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How to Order and Format Author Names in Scientific Papers

As the world becomes more interconnected, the production of knowledge increasingly relies on collaboration. Scientific papers, the primary medium through which researchers communicate their findings, often feature multiple authors. However, authorship isn't merely a reflection of those who contributed to a study but often denotes prestige, recognition, and responsibility. In academic papers, the order of authors is not arbitrary. It can symbolize the level of contribution and the role played by each author in the research process. Deciding on the author order can sometimes be a complex and sensitive issue, making it crucial to understand the different roles and conventions of authorship in scientific research. This article will explore the various types of authors found in scientific papers, guide you on how to correctly order and format author names, and offer insights to help you navigate this critical aspect of academic publishing.

The first author

The first author listed in a scientific paper is typically the person who has made the most substantial intellectual contribution to the work. This role is often filled by a junior researcher such as a Ph.D. student or postdoctoral fellow, who has been intimately involved in almost every aspect of the project.

The first author usually plays a pivotal role in designing and implementing the research, including the formation of hypotheses, experimental design, data collection, data analysis, and interpretation of the findings. They also commonly take the lead in manuscript preparation, writing substantial portions of the paper, including the often-challenging task of turning raw data into a compelling narrative.

In academia, first authorship is a significant achievement, a clear demonstration of a researcher's capabilities and dedication. It indicates that the researcher possesses the skills and tenacity to carry a project from inception to completion. This position can dramatically impact a researcher's career trajectory, playing a critical role in evaluations for promotions, grants, and future academic positions.

However, being the first author is not just about prestige or professional advancement. It carries a weight of responsibility. The first author is generally expected to ensure the integrity and accuracy of the data presented in the paper. They are often the person who responds to reviewers' comments during the peer-review process and makes necessary revisions to the manuscript.

Also, as the first author, it is typically their duty to address any questions or critiques that may arise post-publication, often having to defend the work publicly, even years after publication.

Thus, first authorship is a role that offers significant rewards but also requires a strong commitment to uphold the principles of scientific integrity and transparency. While it's a coveted position that can be a steppingstone to career progression, the associated responsibilities and expectations mean that it should not be undertaken lightly.

The middle authors

The middle authors listed on a scientific paper occupy an essential, albeit sometimes ambiguous, role in the research project. They are typically those who have made significant contributions to the project, but not to the extent of the first author. This group often includes a mix of junior and senior researchers who have provided key input, assistance, or resources to the project.

The roles of middle authors can be quite diverse. Some might be involved in specific aspects of data collection or analysis. Others may bring specialized knowledge or technical skills essential to the project, providing expertise in a particular methodology, statistical analysis, or experimental technique. There might also be middle authors who have contributed vital resources to the project, such as unique reagents or access to a particular patient population.

In some fields, the order of middle authors reflects the degree of their contribution. The closer a middle author is to the first position, the greater their involvement, with the second author often having made the next largest contribution after the first author. This order may be negotiated among the authors, requiring clear communication and consensus.

However, in other disciplines, particularly those where large collaborative projects are common, the order of middle authors may not necessarily reflect their level of contribution. In such cases, authors might be listed alphabetically, or by some other agreed-upon convention. Therefore, it's crucial to be aware of the norms in your specific field when deciding the order of middle authors.

Being a middle author in a scientific paper carries less prestige and responsibility than being a first or last author, but it is by no means a minor role. Middle authors play a crucial part in the scientific endeavor, contributing essential expertise and resources. They are integral members of the research team whose collective efforts underpin the progress and achievements of the project. Without their diverse contributions, the scope and impact of scientific research would be significantly diminished.

The last author

In the listing of authors on a scientific paper, the final position carries a unique significance. It is typically occupied by the senior researcher, often the head of the laboratory or the principal investigator who has supervised the project. While they might not be involved in the day-to-day aspects of the work, they provide overarching guidance, mentorship, and often the resources necessary for the project's fruition.

The last author's role is multidimensional, often balancing the responsibilities of project management, funding acquisition, and mentorship. They guide the research's direction, help troubleshoot problems, and provide intellectual input to the project's design and interpretation of results. Additionally, they usually play a key role in the drafting and revision of the manuscript, providing critical feedback and shaping the narrative.

In academia, the last author position is a symbol of leadership and scientific maturity. It indicates that the researcher has progressed from being a hands-on contributor to someone who can guide a team, secure funding, and deliver significant research projects. Being the last author can have substantial implications for a researcher's career, signaling their ability to oversee successful projects and mentor the next generation of scientists.

However, along with prestige comes significant responsibility. The last author is often seen as the guarantor of the work. They are held accountable for the overall integrity of the study, and in cases where errors or issues arise, they are expected to take the lead in addressing them.

The convention of the last author as the senior researcher is common in many scientific disciplines, especially in the life and biomedical sciences. However, it's important to note that this is not a universal standard. In some fields, authors may be listed purely in the order of contribution or alphabetically. Therefore, an understanding of the specific norms and expectations of your scientific field is essential when considering author order.

In sum, the position of the last author, much like that of the first author, holds both honor and responsibility, reflecting a leadership role that goes beyond mere intellectual contribution to include mentorship, management, and accountability.

Formatting author names

When it comes to scientific publishing, details matter, and one such detail is the correct formatting of author names. While it may seem like a minor concern compared to the intellectual challenges of research, the proper formatting of author names is crucial for several reasons. It ensures correct attribution of work, facilitates accurate citation, and helps avoid confusion among researchers in the same field. This section will delve deeper into the conventions for formatting author names, offering guidance to ensure clarity and consistency in your scientific papers.

Typically, each author's full first name, middle initial(s), and last name are listed. It's crucial that the author's name is presented consistently across all their publications to ensure their work is correctly attributed and easily discoverable.

Here is a basic example following a common convention:

• Standard convention: John D. Smith

However, conventions can vary depending on cultural naming practices. In many Western cultures, the first name is the given name, followed by the middle initial(s), and then the family name. On the other hand, in many East Asian cultures, the family name is listed first.

Here is an example following this convention:

• Asian convention: Wang Xiao Long

When there are multiple authors, their names are separated by commas. The word "and" usually precedes the final author's name.

Here's how this would look:

• John D. Smith, Jane A. Doe, and Richard K. Jones

However, author name formatting can differ among journals. Some may require initials instead of full first names, or they might have specific guidelines for handling hyphenated surnames or surnames with particles (e.g., "de," "van," "bin"). Therefore, it's always important to check the specific submission guidelines of the journal to which you're submitting your paper.

Moreover, the formatting should respect each author's preferred presentation of their name, especially if it deviates from conventional Western naming patterns. As the scientific community becomes increasingly diverse and global, it's essential to ensure that each author's identity is accurately represented.

In conclusion, the proper formatting of author names is a vital detail in scientific publishing, ensuring correct attribution and respect for each author's identity. It may seem a minor point in the grand scheme of a research project, but getting it right is an essential part of good academic practice.

The concept of authorship in scientific papers goes well beyond just listing the names of those involved in a research project. It carries critical implications for recognition, responsibility, and career progression, reflecting a complex nexus of contribution, collaboration, and intellectual leadership. Understanding the different roles, correctly ordering the authors, and appropriately formatting the names are essential elements of academic practice that ensure the rightful attribution of credit and uphold the integrity of scientific research.

Navigating the terrain of authorship involves managing both objective and subjective elements, spanning from the universally acknowledged conventions to the nuances particular to different scientific disciplines. Whether it's acknowledging the pivotal role of the first author who carried the project from the ground up, recognizing the valuable contributions of middle authors who provided key expertise, or highlighting the mentorship and leadership role of the last author, each position is an integral piece in the mosaic of scientific authorship.

Furthermore, beyond the order of authors, the meticulous task of correctly formatting the author names should not be underestimated. This practice is an exercise in precision, respect for individual identity, and acknowledgement of cultural diversity, reflecting the global and inclusive nature of contemporary scientific research.

As scientific exploration continues to move forward as a collective endeavor, clear and equitable authorship practices will remain crucial. These practices serve not only to ensure that credit is assigned where it's due but also to foster an environment of respect and transparency. Therefore, each member of the scientific community, from fledgling researchers to seasoned scientists, would do well to master the art and science of authorship in academic publishing. After all, it is through this collective recognition and collaboration that we continue to expand the frontiers of knowledge.

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Defining authorship in your research paper

Co-authors, corresponding authors, and affiliations, why does authorship matter.

Authorship gives credit and implies accountability for published work, so there are academic, social and financial implications.

It is very important to make sure people who have contributed to a paper, are given credit as authors. And also that people who are recognized as authors, understand their responsibility and accountability for what is being published.

There are a couple of types of authorship to be aware of.

Co-author Any person who has made a significant contribution to a journal article. They also share responsibility and accountability for the results of the published research.

Corresponding author If more than one author writes an article, you’ll choose one person to be the corresponding author. This person will handle all correspondence about the article and sign the publishing agreement on behalf of all the authors. They are responsible for ensuring that all the authors’ contact details are correct, and agree on the order that their names will appear in the article. The authors also will need to make sure that affiliations are correct, as explained in more detail below.

Open access publishing

There is increasing pressure on researchers to show the societal impact of their research.

Open access can help your work reach new readers, beyond those with easy access to a research library.

How common is co-authorship and what are the challenges collaborating authors face? Our white paper  Co-authorship in the Humanities and Social Sciences: A global view explores the experiences of 894 researchers from 62 countries.

If you are a named co-author, this means that you:

Made a significant contribution to the work reported. That could be in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas.

Have drafted or written, substantially revised or critically reviewed the article.

Have agreed on the journal to which the article will be submitted.

Reviewed and agreed on all versions of the article before submission, during revision, the final version accepted for publication, and any significant changes introduced at the proofing stage.

Agree to take responsibility and be accountable for the contents of the article. Share responsibility to resolve any questions raised about the accuracy or integrity of the published work.

Every submission to our medical and health science journals should comply with the International Committee on Medical Journal Ethics’  definition of authorship .

Please include any other form of specific personal contribution in the acknowledgments section of your paper.

Affiliations: get it right

Your affiliation in the manuscript should be the institution where you conducted the research. You should also include details of any funding received from that institution.

If you have changed affiliation since completing the research, your new affiliation can be acknowledged in a note. We can’t normally make changes to affiliation after the journal accepts your article.

Changes to authorship

Authorship changes post-submission should only be made in exceptional circumstances, and any requests for authors to be removed or added must be in line with our authorship criteria.  

If you need to make an authorship change, you will need to contact the Journal Editorial Office or Editorial team in the first instance. You will be asked to complete our Authorship Change request form ; all authors (including those you are adding or removing) must sign this form. This will be reviewed by the Editor (and in some instances, the publisher). 

Please note any authorship change is at the Editor’s discretion; they have the right to refuse any authorship change they do not believe conforms with our authorship policies. 

Some T&F journals do not allow any authorship changes post-submission; where this is applicable, this will be clearly indicated on the journal homepage or on the ‘instructions for authors’ page. 

If the corresponding author changes before the article is published (for example, if a co-author becomes the corresponding author), you will need to write to the editor of the journal and the production editor. You will need to confirm to them that both authors have agreed the change.

Requested changes to the co-authors or corresponding authors following publication of the article may be considered, in line with the  authorship guidelines issued by COPE , the Committee on Publication Ethics. Please  see our corrections policy  for more details. Any requests for changes must be made by submitting the completed  Authorship Change Request form .

Authorship Change Request form

Important: agree on your corresponding author and the order of co-authors, and check all affiliations and contact details before submitting.

Taylor & Francis Editorial Policies on Authorship

The following instructions (part of our  Editorial Policies ) apply to all Taylor & Francis Group journals.

Corresponding author

Co-authors must agree on who will take on the role of corresponding author. It is then the responsibility of the corresponding author to reach consensus with all co-authors regarding all aspects of the article, prior to submission. This includes the authorship list and order, and list of correct affiliations.

The corresponding author is also responsible for liaising with co-authors regarding any editorial queries. And, they act on behalf of all co-authors in any communication about the article throughout: submission, peer review, production, and after publication. The corresponding author signs the publishing agreement on behalf of all the listed authors.

AI-based tools and technologies for content generation

Authors must be aware that using AI-based tools and technologies for article content generation, e.g. large language models (LLMs), generative AI, and chatbots (e.g. ChatGPT), is not in line with our authorship criteria.

All authors are wholly responsible for the originality, validity and integrity of the content of their submissions. Therefore, LLMs and other similar types of tools do not meet the criteria for authorship.

Where AI tools are used in content generation, they must be acknowledged and documented appropriately in the authored work.

Changes in authorship

Any changes in authorship prior to or after publication must be agreed upon by all authors – including those authors being added or removed. It is the responsibility of the corresponding author to obtain confirmation from all co-authors and to provide a completed Authorship Change Request form to the editorial office.

If a change in authorship is necessary after publication, this will be amended via a post-publication notice. Any changes in authorship must comply with our criteria for authorship. And requests for significant changes to the authorship list, after the article has been accepted, may be rejected if clear reasons and evidence of author contributions cannot be provided.

Assistance from scientific, medical, technical writers or translators

Contributions made by professional scientific, medical or technical writers, translators or anyone who has assisted with the manuscript content, must be acknowledged. Their source of funding must also be declared.

They should be included in an ‘Acknowledgments’ section with an explanation of their role, or they should be included in the author list if appropriate.

Authors are advised to consult the  joint position statement  from American Medical Writers Association (AMWA), European Medical Writers Association (EMWA), and International Society of Medical Publication Professionals (ISMPP).

Assistance with experiments and data analysis

Any significant contribution to the research reported, should be appropriately credited according to our authorship criteria.

If any parts of the research were outsourced to professional laboratories or to data analysts, this should be clearly stated within the manuscript, alongside an explanation of their role. Or, they should be included in the author list if appropriate.

Authors are responsible for retaining all of the original data related to their work, and should be prepared to share it with the journal editorial office if requested.

Acknowledgments

Any individuals who have contributed to the article (for example, technical assistance, formatting-related writing assistance, translators, scholarly discussions which significantly contributed to developing the article), but who do not meet the criteria for authorship, should be listed by name and affiliation in an ‘Acknowledgments’ section.

It is the responsibility of the authors to notify and obtain permission from those they wish to identify in this section. The process of obtaining permission should include sharing the article, so that those being identified can verify the context in which their contribution is being acknowledged.

Any assistance from AI tools for content generation (e.g. large language models) and other similar types of technical tools which generate article content, must be clearly acknowledged within the article. It is the responsibility of authors to ensure the validity, originality and integrity of their article content. Authors are expected to use these types of tools responsibly and in accordance with our editorial policies on authorship and principles of publishing ethics.

Biographical note

Please supply a short biographical note for each author. This could be adapted from your departmental website or academic networking profile and should be relatively brief (e.g. no more than 200 words).Authors are responsible for retaining all of the original data related to their work, and should be prepared to share it with the journal editorial office if requested.

Author name changes on published articles

There are many reasons why an author may change their name in the course of their career. And they may wish to update their published articles to reflect this change, without publicly announcing this through a correction notice. Taylor & Francis will update journal articles where an author makes a request for their own name change, full or partial, without the requirement for an accompanying correction notice. Any pronouns in accompanying author bios and declaration statements will also be updated as part of the name change, if required.

When an author requests a name change, Taylor & Francis will:

Change the metadata associated with the article on our Taylor & Francis Online platform.

Update the HTML and PDF version of the article.

Resupply the new metadata and article content to any abstracting and indexing services that have agreements with the journal. Note: such services may have their own bibliographic policies regarding author name changes. Taylor \u0026amp; Francis cannot be held responsible for controlling updates to articles on third party sites and services once an article has been disseminated.

If an author wishes for a correction notice to be published alongside their name change, Taylor & Francis will accommodate this on request. But, it is not required for an author name change to be made.

To request a name change, please contact your Journal’s Production Editor or contact us.

Taylor & Francis consider it a breach of publication ethics to request a name change for an individual without their explicit consent.

Additional resources

Co-authorship in the Humanities and Social Sciences  – our white paper based on a global survey of researchers’ experiences of collaboration.

Discussion Document: Authorship  – produced by COPE (Committee on Publication Ethics), this updated guide includes practical advice on addressing the most common ethical issues in this area

Taylor & Francis Editorial Policies

Ethics for authors  – guidelines, support, and your checklist.

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For more information about FWCI, see What is Field-weighted Citation Impact (FWCI)?

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One of the first things to look for is the author or authors. In a research article, the authors will list their affiliation, usually with a university or research institution. In this example, the author's affiliation is clearly shown on the first page of the article. In a research article, you will never have an anonymous author or need to look for the author's name or affiliation.

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How to Order Authors in Scientific Papers

It’s rare that an article is authored by only one or two people anymore. In fact, the average original research paper has five authors these days. The growing list of collaborative research projects raises important questions regarding the author order for research manuscripts and the impact an author list has on readers’ perceptions.

With a handful of authors, a group might be inclined to create an author name list based on the amount of work contributed. What happens, though, when you have a long list of authors? It would be impractical to rank the authors by their relative contributions. Additionally, what if the authors contribute relatively equal amounts of work? Similarly, if a study was interdisciplinary (and many are these days), how can one individual’s contribution be deemed more significant than another’s?

Why does author order matter?

Although an author list should only reflect those who have made substantial contributions to a research project and its draft manuscript (see, for example, the authorship guidelines of the International Committee of Medical Journal Editors ), we’d be remiss to say that author order doesn’t matter. In theory, everyone on the list should be credited equally since it takes a team to successfully complete a project; however, due to industry customs and other practical limitations, some authors will always be more visible than others.

The following are some notable implications regarding author order.

• The “first author” is a coveted position because of its increased visibility. This author is the first name readers will see, and because of various citation rules, publications are usually referred to by the name of the first author only. In-text or bibliographic referencing rules, for example, often reduce all other named authors to “et al.” Since employers use first-authorship to evaluate academic personnel for employment, promotion, and tenure, and since graduate students often need a number of first-author publications to earn their degree, being the lead author on a manuscript is crucial for many researchers, especially early in their career.
• The last author position is traditionally reserved for the supervisor or principal investigator. As such, this person receives much of the credit when the research goes well and the flak when things go wrong. The last author may also be the corresponding author, the person who is the primary contact for journal editors (the first author could, however, fill this role as well, especially if they contributed most to the work).
• Given that there is no uniform rule about author order, readers may find it difficult to assess the nature of an author’s contribution to a research project. To address this issue, some journals, particularly medical ones, nowadays insist on detailed author contribution notes (make sure you check the target journal guidelines before submission to find out how the journal you are planning to submit to handles this). Nevertheless, even this does little to counter how strongly citation rules have enhanced the attention first-named authors receive.

Common Methods for Listing Authors

The following are some common methods for establishing author order lists.

• Relative contribution. As mentioned above, the most common way authors are listed is by relative contribution. The author who made the most substantial contribution to the work described in an article and did most of the underlying research should be listed as the first author. The others are ranked in descending order of contribution. However, in many disciplines, such as the life sciences, the last author in a group is the principal investigator or “senior author”—the person who often provides ideas based on their earlier research and supervised the current work.
• Alphabetical list . Certain fields, particularly those involving large group projects, employ other methods . For example, high-energy particle physics teams list authors alphabetically.
• Multiple “first” authors . Additional “first” authors (so-called “co-first authors”) can be noted by an asterisk or other symbols accompanied by an explanatory note. This practice is common in interdisciplinary studies; however, as we explained above, the first name listed on a paper will still enjoy more visibility than any other “first” author.
• Multiple “last” authors . Similar to recognizing several first authors, multiple last authors can be recognized via typographical symbols and footnotes. This practice arose as some journals wanted to increase accountability by requiring senior lab members to review all data and interpretations produced in their labs instead of being awarded automatic last-authorship on every publication by someone in their group.
• Negotiated order . If you were thinking you could avoid politics by drowning yourself in research, you’re sorely mistaken. While there are relatively clear guidelines and practices for designating first and last authors, there’s no overriding convention for the middle authors. The list can be decided by negotiation, so sharpen those persuasive argument skills!

As you can see, choosing the right author order can be quite complicated. Therefore, we urge researchers to consider these factors early in the research process and to confirm this order during the English proofreading process, whether you self-edit or received manuscript editing or paper editing services , all of which should be done before submission to a journal. Don’t wait until the manuscript is drafted before you decide on the author order in your paper. All the parties involved will need to agree on the author list before submission, and no one will want to delay submission because of a disagreement about who should be included on the author list, and in what order (along with other journal manuscript authorship issues).

On top of that, journals sometimes have clear rules about changing authors or even authorship order during the review process, might not encourage it, and might require detailed statements explaining the specific contribution of every new/old author, official statements of agreement of all authors, and/or a corrigendum to be submitted, all of which can further delay the publication process. We recommend periodically revisiting the named author issue during the drafting stage to make sure that everyone is on the same page and that the list is updated to appropriately reflect changes in team composition or contributions to a research project.

Educational resources and simple solutions for your research journey

Author Affiliations in Research Papers: Answering Your Top 3 Queries

Author affiliation in research papers is an important element because it offers readers useful information about where the research was conducted. However, the time from research to manuscript creation and then publication is so long that by the time the research paper is published authors may have moved to a different institution or location.

In such cases, researchers may have questions about how these affiliation changes could be handled because it’s important for readers to know both old and new author affiliations in research papers. This article aims to answer a few common questions researchers may have regarding this process.

Table of Contents

1. Do I need an affiliation for journal publication ? Can I list multiple author affiliations in research papers ? 1

In academic publishing, an affiliation is the university or institution to which an author belongs or where authors have conducted a major part of the research that is discussed in their paper. Author affiliation in research papers is usually listed after the author names and provide credibility to the research and give readers confidence that the research is backed by an institution or university. The name of the institution clarifies who oversees the research integrity because these institutes usually have review boards that approve the research conducted at their institute. Because of the increase in the number of international collaborations among authors, an individual author may have multiple affiliations, all of which must be listed in the paper to ensure transparency. However, while some manuals or journal style guides may restrict the number of affiliations per author (e.g., APA manual, 7 th ed, no more than 2 affiliations per author; AMA style manual, no more than 1 or 2 affiliations per author in some types of manuscripts like viewpoints or research letters), other journals may have no such restrictions. 2  

2. What should my author affiliation in research papers be if my workplace changes after manuscript submission? Can/should I mention both old and new author affiliations in research papers ? 3

Usually, it is acceptable to mention both current and previous author affiliations in research papers. In general, if your research was primarily conducted at your previous institution using its resources, then this institute should definitely be included in the author affiliations. This same institution should also be mentioned in the Materials and Methods section of your paper and as the sponsor of your work. However, the name of your current institute should also be mentioned so that readers could contact you if required. Different journals or publishers may have different rules for listing old and new author affiliations in research papers, so it is always advisable to consult the specific journal’s instructions for authors.

Here are a few examples of how different publishers or journals address pre- and post-submission changes in author affiliations in research papers :  

• The American Medical Association’s style manual (11 th edition): As per the American Medical Association’s style manual’s rules for author affiliation in research papers, if the author has moved after submitting a manuscript, the current affiliation should still be provided to the journal so that it could be added to the list of affiliations.
• Cambridge University Press : As per the Cambridge University Press’s rules for author affiliation in research papers, if an author has moved before manuscript submission, the current affiliation could be included under Acknowledgments.
• Sage journals : As per Sage journals ’ rules for author affiliation in research papers, an author must include new affiliations after submission as a note at the end of the manuscript. 
• American Chemical Society Publications, Wiley : As per American Chemical Society Publication’s rules for author affiliation in research papers, if the current address of the author is different from the one where the research was conducted, then this current address should be included in a footnote on the title page. 

3. Is it possible to change author affiliation in research papers after the manuscript is accepted/has already been published?  

Most journals accept requests for changes in author affiliation in research papers after acceptance , although there are a few exceptions. However, once an article has been published, changes may not necessarily be accepted or may require special permission and approval from the journal editor.  

Listed below are a few examples of how different publishers address post-acceptance or post-publication requests for changes in author affiliation in research papers :  

• Cambridge University Press : 4 May accept an affiliation change request after submission in the event of a genuine reason. If the article has been published, a change in author affiliation in research papers would require the publishing of a linked correction notice.  
• Taylor and Francis : 5 If the authors have changed affiliations since completing their research, then the new affiliation can be acknowledged in a note; however, they don’t usually make changes to affiliations after accepting a manuscript for publication.  
• Springer : 6 Do not update or change affiliations once an article has been published.  

Author affiliations in research papers constitute an important part of the author information and should be mentioned accurately and clearly for all authors. Always refer to the journal or publisher’s instructions for authors for up-to-date information on the format for writing author affiliations in research papers . We hope this article has elaborated the importance of affiliations for journal publication and helped clarify any questions about handling changes in them.  

Other Frequently Asked Questions (FAQ)

Q: What does author affiliation in research paper mean?

Author affiliation in research papers refers to the academic, research, or professional institutions to which the paper’s authors are affiliated. Usually mentioned below the author’s name, author affiliation in research papers are important as they provide important information about the author’s background and the context in which the research was conducted. Author affiliations help identify experts in specific fields or disciplines. They establish the credibility and trustworthiness of the research, and affiliations with top institutions add weight to the author’s work and indicate a higher level of expertise and academic rigor. This information also allows readers to identify potential conflicts of interest or connections, which fosters collaborations that further scientific progress.

Q: What is the first author’s affiliation?

The first author affiliation in a research paper refers to the institution or organization to which the lead author is primarily affiliated. The first author is the individual who makes the most substantial contribution to the research work, hence their affiliation is significant. This detail serves as an indicator of the research environment and resources available for the research project, which can bolster the credibility, reach, and impact of the research paper.

Q: Can an author have two affiliations?

Yes, it is possible for an author to have two or more affiliations. Authors may have joint appointments or collaborations between different institutions, allowing them to be affiliated with multiple organizations simultaneously. In such cases, authors often indicate their affiliations using superscript numbers or symbols to denote different institutions. This information helps readers understand the diverse institutional connections and collaborations of the authors.

References  

• E. Bik. False affiliations and fake authors. Science Integrity Digest. Accessed December 15, 2022. https://scienceintegritydigest.com/2019/06/04/false-affiliations-and-fake-authors/  
• American Medical Association style manual. 11 TH edition, Section 2.3.3  
• Q&A Forum. Editage Insights. Accessed December 16, 2022. https://www.editage.com/insights/what-should-my-affiliation-be-if-i-changed-my-workplace-during-a-manuscript-submission  
• Author affiliations. Cambridge University Press. Accessed December 15, 2022. https://www.cambridge.org/core/services/authors/journals/author-affiliations#1a  
• Defining authorship in your research paper. Author services: Taylor & Francis. https://authorservices.taylorandfrancis.com/editorial-policies/defining-authorship-research-paper/  
• Authorship principles. Springer. Accessed December 15, 2022. https://www.springer.com/gp/editorial-policies/authorship-principles  

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Publication ethics: Role and responsibility of authors

Shubha singhal.

Department of Pharmacology, Maulana Azad Medical College, New Delhi, 110 002 India

Bhupinder Singh Kalra

Publication of scientific paper is critical for modern science evolution, and professional advancement. However, it comes with many responsibilities. An author must be aware of good publication practices. While refraining from scientific misconduct or research frauds, authors should adhere to Good Publication Practices (GPP). Publications which draw conclusions from manipulated or fabricated data could prove detrimental to society and health care research. Good science can blossom only when research is conducted and documented with complete honesty and ethics. Unfortunately, publish or perish attitude has led to unethical practices in scientific research and publications. There is need to identify, acknowledge, and generate awareness among junior researchers or postgraduate students to curb scientific misconduct and adopt GPP. This article discusses various unethical publication practices in research. Also, the role and responsibilities of authors have been discussed with the purpose of maintaining the credibility and objectivity of publication.

Introduction

Need to publish.

A scientific paper is an organized description of hypothesis, data, and conclusions, intended to instruct the readers. Research conducted has to be published or documented; otherwise, it is considered not done. Publication of paper is critical for the evolution of modern science, in which the work of one scientist builds upon that of others [ 1 ]. The roots of scholarly, scientific publishing can be traced to 1665, when Henry Oldenburg of the British Royal Society established the journal Philosophical Transactions of the Royal Society . The aim of the journal was to create a public record of original contribution to knowledge and also to encourage scientists to “speak” directly to others [ 2 ]. Documentation of research work followed by publication helps in the dissemination of observations and findings. This flow of knowledge guides and contributes towards research coalition. Established and budding researchers do get benefited by published literature and consolidates their research.

Publication of research in peer-reviewed journal not only validates the research and boosts confidence of the authors but also gives national and international recognition to an author, department, university, and institution [ 3 ]. Unfortunately, in some establishments, the most compelling reason for publication is to fulfill specific job requirements by employers. It may include promotion to an academic position and improving prospects of success in research grant application. The importance of publication in the career is further emphasized by the adage “Publish or perish,” i.e. publish your research or lose your identity.

Ethics-related organizations and their role

A good research involves many coordinated steps. It starts from hypothesis, selection of appropriate study design, study execution, data collection, analysis, and finally publication. Not only the conduct of the study requires ethics to be adhered to but also the process of publication comes under the purview of ethics. Any publication that reports the results and draws the conclusion from the data which have been manipulated is considered research fraud or scientific misconduct [ 4 ]. Recently, Lancet retracted a study entitled “Hydroxychloroquine or chloroquine with or without a macrolide for treatment of COVID-19: a multinational registry analysis” because the veracity of the data underlying this observational study could not be assured by the study authors [ 5 ].

There are organizations which give recommendations and develop guidelines to assist authors, editors, and reviewers. The purpose is to create and disseminate accurate, clear, reproducible, unbiased research papers. The organizations involved with publication ethics are

• International Committee of Medical Journals Editors (ICMJE).
• World Association of Medical Editors (WAME)
• Committee on Publication Ethics (COPE)

The ICMJE was established in 1978, in Vancouver, British Columbia, Canada, by a group of medical journal editors. ICMJE developed recommendations which are primarily for authors who want to submit their work in ICMJE member journals. These recommendations discuss the role and responsibilities of the authors, contributors, reviewers, and editors. Steps of manuscript preparation, submission, and editorial issues related to publication in medical journals are also discussed and drafted. The uniform requirements for manuscript submitted to biomedical journals, which most of the journals are following were drafted by ICMJE [ 6 ].

The WAME is a nonprofit voluntary association, which was established in 1995 by a group of members of the ICMJE. The goal was to improve editorial standards, promote professionalism in medical editing, and encourage research on the principals and practice of medical editing. The role of WAME is to facilitate worldwide cooperation and communication among editors of peer-reviewed medical journal. Membership in WAME is free and all decision-making editors of peer-reviewed journals are eligible to join. WAME has more than 1830 members representing more than 1000 journals from 92 countries [ 7 ].

The COPE also helps in ethical publication. COPE was founded in 1997 by a small number of UK medical editors as a self-help group to discuss troubling ethical cases in the publication process. It provides paid membership and currently has more than 7000 members in various disciplines from all parts of the world. The purpose of COPE is to find the practical ways to deal with the misconduct cases and to develop codes of conduct for good publication practice. It also generates the funding for the research based on the issues related to publication misconduct [ 8 ].

Process of publication

The scientific publication is a team effort. Transforming the research findings and observations into a published article is an art as well as science, which involves multiple steps. The very first step is the preparation of the manuscript as per the journal’s requirement. The language in which the manuscript has been drafted is important. It should be checked by an expert or native language speaker and the senior authors. Clear and concise language helps editors and reviewers to concentrate on the content. For up-to-date information, recent references should be cited. Final manuscript must be shared with all the authors and it should have approval of all the authors. Copyright transfer form should be signed by all the authors before submitting to the journal. Signing the copyright form brings responsibility.

Submitted manuscripts are first screened by the editors for its suitability, content, novelty, and what it adds to existing knowledge. The subject of research work should be synchronized with the target journal. It should comply with journal’s manuscript drafting guidelines. After the editorial screening, if some technical issues or non-adherence to manuscript guidelines are observed, it is sent back to the author for technical modifications. The peer review process gets initiated after technical modifications are acceptable. It may take a couple of weeks/months.

In light of reviewer’s recommendations, the editor sends the decision letter to the author mentioning the status of the manuscript, i.e. accepted, rejected, or requires revision. In case of revision, author(s) reply in detail to all comments of reviewers and submit to the journal again within stipulated time. After deliberation on replies and revised manuscript submitted, the editor decides for suitability of publication or if it needs to be sent out for review again. These steps get repeated until the manuscript is accepted or rejected. Once it gets accepted, it goes under proof read stage and finally gets published. The author is never in direct communication with the reviewer. He communicates with the Editorial board only. The reviewer should declare conflicts of interest (COI), if any, before reviewing the manuscript. Manuscripts are usually mailed to reviewers without information of the authors and their affiliations; hence, reviewers are blinded.

What is publishable or not publishable?

Writing for publication is an important yet challenging form of knowledge dissemination. Journals like to publish articles that present an exhaustive meaningful research. It should contribute towards the knowledge building and awareness of readers. At the very minimum, a publishable article needs to be original. It should be conducted and drafted with robust methodology and significant findings, well organized, well written, and concise yet clear. It should be drafted with clear explanation of how the article addresses the existing knowledge gap. Conclusion drawn should be relevant to the audience or readers with a comprehensive list of up-to-date references. Papers that are poorly organized, cluttered with unnecessary information, and consist of routine extension of previous reports or fragmentary reports of research results are not accepted for publication. Violation of ethical or legal norms, including plagiarism, duplicates publication lead to immediate rejection of the paper [ 9 ].

Scientific misconduct

Scientific misconduct is the violation of the standard codes of scholarly conduct and ethical behavior in the publication of scientific research [ 10 ]. Misconduct in the scientific publication process by the authors is detrimental for integrity of the whole system and is considered unethical. Falsification or fabrication of data is the gravest form of scientific misconduct wherein authors either manipulate skewed data to look favorable or generate data where no data exists. Different forms of scientific misconduct are plagiarism or misappropriation of the ideas of others, improprieties of authorship, simultaneous publications, duplicate publications, salami slicing, and non-declaration of COI. Conducting research without informed consent or ethics approval and not maintaining data confidentiality is a form of scientific misconduct. Editors or publication houses do take disciplinary action as per COPE recommendations against scientific misconduct. Authors are blacklisted or banned to submit articles in the respective journal in the future [ 11 ].

Criteria of authorship

Academic life revolves around publications. The publication adds to the credibility of the research and brings fame and recognition. An author is an individual who fulfills enlisted criteria collectively: (1) substantial contributions to conception and design; (2) acquisition of data, or analysis and interpretation of data; (2) drafting the article or revising it critically for important intellectual content; and (3) final approval of the version to be published. Individuals who have provided technical services/translating text/identifying patients for study/supplying material/providing funds/applied statistics/medical writers are not eligible for authorship. However, all those contributors who do not meet the criteria for authorship should be listed in the acknowledgement section [ 12 , 13 ]. Because of the important role of publication in clinical practice and academic setting, the authorship of articles must be honest, reliable, trustworthy, and transparent.

Types of authors

Since authorship is sought after, many unethical practices are also prevalent. Ghost, guest, or gift authors are the examples of such practices. A ghost author is a person who has made a substantial contribution to the research or writing of a manuscript but is not listed as an author. A ghost author might be a direct employee or hired contract employee of pharmaceutical company and hence, listing him as an author amounts to COI [ 14 ]. It is dishonest to omit an author who has made significant contributions. In contrast to ghost author, guest or gift/honorary author is someone who is named as an author, but who did not contribute in a meaningful way to the design, research, analysis, or writing of a paper. Often guest or gift authors are well known and well respected in the field of research. The inclusion of their name in the author list might increase chances of acceptance for publication.

However, sometimes senior investigators may also give honorary authorship to their colleagues for encouraging collaborations and maintaining good working relations or as repayment of favors. Whatever the cause, the gift or guest authorship is an unacceptable practice in publication. The presence of well-known author on the board as a guest author can influence the opinion of clinicians, academicians, and politicians about a particular drug or device. Secondly, due to gift authorship, the person is perceived as being more skilled than his colleague who has not published [ 12 , 13 ]. In multicenter trials, since investigators from different sites have contributed, they qualify for the authorship and all those who qualify for authorship should be listed [ 15 ]. One should always remember that authorship brings responsibility and authors have to be accountable to the data and results which are published.

Authorship issues/disputes

Authorship issues or disputes account for 2% to 11% of all disagreement in the scientific community. The authorship disputes could range from order of authorship, inclusion or exclusion of authors, number of authors etc. Request for addition of authors after submission or even after publication is quite common. In contrast, there are examples where a co-author denies becoming a part of a manuscript, once any scientific misconduct including plagiarism is detected [ 16 ].

The order of authorship should be mutually decided before taking up the study. It has to be a joint decision of all co-authors. In multicenter trials, research group includes large number of researchers. Hence, the corresponding author specifies and registers the group name and clearly identifies the group members who can take credit and responsibility for the work as an author.

ICMJE and other organizations issued the guidelines regarding group authorship and stated that in case of group authorship the byline of the article identifies who is directly responsible for the manuscript, and MEDLINE lists as authors. If the byline includes a group name, MEDLINE will list the names of individual group members who are authors or who are collaborators [ 17 ]. Despite these guidelines, authorship battles for inappropriate attribution of credit are witnessed in this area also.

Usually, the dispute is for the “First author” place because most of the articles are cited by the name of the first author. Conventionally, the extent of involvement decides the order of authorship; for example, the person who has done the majority of the groundwork would be considered eligible for being the first author (junior researcher) and the person who planned and conceived the study would be the last author (supervisor). There is no general consensus in order of authorship, and there are different schools of thoughts [ 16 ]. During submission of revised manuscript, order of authorship should not be altered without any justification. Approval from all authors is warranted in case of revision of order of authorship. It affects the credibility of manuscript too.

How to resolve authorship issues

The best way to prevent disputes in authorship is to generate awareness among research groups about authorship criteria and to develop Standard Operating Procedure (SOP) for the conduct and publication of research. COPE guidelines are to be referred in case of authorship or conflicts [ 18 ]. The next best option to prevent disputes is to have open discussion among all the authors involved in multidisciplinary research prior to initiating research, i.e. at the time of protocol drafting. Defining the role and responsibility of each author further reduces the chances of disputes within the research team. Editors do ask for individual contributions of authors in designing manuscript. The journal can blacklist guest or ghost authors [ 12 ].

Plagiarism: do’s and don’ts

The word plagiarism was first used in the English language in the year 1601 by the dramatist Ben Jonson to describe someone who was guilty of theft. Plagiarism is derived from the Latin word “plagiare” which means to “kidnap.” A plagiarist is the person who commits plagiarism [ 19 ]. By definition, plagiarism is the use of previously published work by another author in one’s own manuscript without consent, credit, or acknowledgement. It is the most common form of scientific misconduct [ 4 ]. Plagiarism can be intentional or unintentional. Unintentional plagiarism is usually seen in articles written by students or junior researchers. Lack of awareness and ignorance lead to unintentional plagiarism. Intentional plagiarism happens when an author deliberately copies documented or published work and presents it as his/her own. Both types of plagiarism are unethical and illegal, which can ruin the career and reputation of the writer [ 19 ].

Plagiarism of idea occurs when a plagiarist copies or steals the idea or thought of someone else and presents it as his/her own. Such type of plagiarism is difficult to detect; however, once detected, it is considered serious offense. The example of plagiarism of idea is presenting or documenting an idea of someone else which is being discussed or presented in any conference or seminar without citing proper sources. Plagiarism of text or direct plagiarism, i.e. word to word writing, is when a researcher takes large section of an article from another source and pastes it in his/her own research without providing proper citation. One of the hybrid varieties of plagiarism is Mosaic plagiarism where the author steals the idea, opinion, words, and phrases from different sources and merges words without acknowledging the original author.

Self-plagiarism is the practice of an author using portions of their previous writings on the same topic in their subsequent publications, without specifically citing it formally in quotes. There is no consensus as to whether this is a form of scientific misconduct, or how many of one’s own words one can use before it is truly “plagiarism.” To be on the safer side, authors should cite source or give reference of their previous publications. There are examples in which plagiarism engulfed the entire career of authors and writers and it became the reason of article retraction or rejection [ 20 ].

Culture of publish or perish is one of the important causes of plagiarism. The researcher needs to publish a large number of papers in limited time period to get more opportunities in career and research. In addition, lack of knowledge, laziness, and fear of failure and desire of getting recognition also lead to plagiarism. Many softwares, which can detect plagiarism are available online. It is the responsibility of the author to run their manuscript through software before submitting it to the journal [ 19 , 21 ].

The very first step to prevent plagiarism is the awareness about plagiarism, the consequences, and how to avoid plagiarism. Authors can avoid plagiarism by acknowledging the original source of the idea or word and enclosing them within quotation marks. In case of paraphrasing, where the writer writes the text in his own word, authors must properly cite the original source. Authors must always obtain permission for use of published illustration. Authors should avoid writing multiple separate articles if he can present a large, complex study in a cohesive manner in a single article [ 21 ].

Conflict of interest

Conflict of interest is an attribute which is invisible to the reader or editor, but which may affect or influence his or her judgment or objectivity. Academicians/physicians and researchers often work in collaboration with pharmaceutical and biotechnology companies to develop a product for the well-being of society. However, there are examples where financial and non-financial ties of researches or physicians with the company have compromised the integrity of research [ 22 ].

Conflict of interest describes the situations where the impartiality of the research may be compromised because the researcher stands to profit in some way from the conclusions they draw [ 23 ]. Examples of potential conflicts of interests that are directly or indirectly related to the research may include research grants from funding agencies, honorarium for speaking at symposium, financial support for educational programs, employment, and multiple affiliations. In addition, non-financial benefits including recognition, career advancement, advocacy for a strongly held position, and support for friends and colleagues can also affect the research work and result biases in the research. These biases, when hidden, can affect clinical decision-making by making interventions appear safer or more effective than they really are [ 24 ].

Disclosure of COI is the basic requirement to prevent attribution-related bias in the research. The ICMJE has produced a common form to disclose any COI and that has to be individually signed by each co-author. It has to be uploaded along with the manuscript files. The intent of the disclosure form is not to prevent authors with a potential COI from publication. It is merely intended that any potential conflict should be declared so that the readers may form their own judgment about the findings and observations. It is for the readers to determine whether the authors outside interest may reflect a possible bias in either the exposition of the conclusions presented [ 25 ]. Authors are supposed to declare COI in the manuscript text too which is meant for readers.

Duplicate publication

Duplicate publication or redundant publication is a publication of a paper that substantially overlaps with one which is already published, without clear, visible reference to the previous publication [ 26 ]. As per copyright law and publication ethics, whatever is available in the journal for reading would be original unless there is a clear statement that the author and editor are intentionally republishing an article. Hence, duplication of publication is the breach in the copyright law and against the ethical conduct. In addition, duplication of publication causes waste of limited resources and also leads to inappropriate weighting of the result of a single study. It was observed that duplicate publications of Ondansetron led to overestimation of its efficacy by 23% in one of the meta-analyses [ 26 , 27 ].

The COPE classifies duplicate publication into major and minor offenses. The major offense is the one where duplicate publication is based on the same data set and findings which are already published. It is also considered if there is evidence that the author tried to hide duplication by changing the title or order of authorship or by not referring previous publication [ 28 ]. Minor or salami slicing is considered segmental publication or part publication of results or reanalysis derived from a single study. Authors do it to increase the number of publications and citations. It is considered unethical and it is taken in a bad taste because for a reader it may cause distortion in the conclusions drawn. Publication of the results of a single study in parts in different journals might lead to over-judgement. Wrong conclusions may be drawn from a study if it is done on a fixed number of subjects but the data are being presented in fragments in different journals.

When an author needs to submit a report that has been already published or closely related to another paper that has been submitted elsewhere, the letter of submission should clearly say so. The authors should declare and provide copies of the related submission to help the editor decide how to handle the submission. Authors who attempt to duplicate publication without such notification can face prompt rejection of the submitted manuscript. If the editor was not aware of the violations and the article has already been published, then the article might warrant retraction with or without the author’s explanation or approval.

Duplicate publication does not prevent the author to disseminate important public health information in case of public health emergency. In fact, ICMJE encourages editors to give priority to authors who have made crucial data publicly available without delay [ 26 ]. Duplicate publications are justified if it is about combined editorials, clinical guidelines, and translation of archives.

Predatory publishing

Predatory publishing is the publication of an article in the journal that lacks the usual feature of editorial oversight, transparent policies, and operating procedure of legitimate peer review journals. Predatory journals exploit the authors by charging the publication fee and deceiving them by providing the false claim about the journal’s impact factor, indexing, and peer review [ 29 ].

Predatory publishing is harmful for both the author and the community. Predatory publishing may tarnish the image of the author. Articles published in predatory journals are usually not appreciated by the subject expert. It can misinform the readers and propagate wrong science because of poor quality control. Sometimes genuine information also gets missed because most of the predatory journals are not indexed in the database, so papers are not easily traceable [ 30 ].

Predatory publishing can be avoided by educating researchers, supervisors, and administrators about fake journals. Authors should also learn how to identify trustworthy journals. If the journal website mentions of indexing, then it is important to cross check the inclusion of the journal in the mentioned databases. For an open-access journal, the inclusion in Directory of Open Access Journals (DOAJ) can be checked at the DOAJ website. The journal’s claim of the Journal Citation Report (JCR) impact factor can be verified by its International Standard Serial Number (ISSN) number in the JCR Master list. Another approach to check trustworthy journals is to self-asses the journal through websites like https://thinkchecksubmit.org/ [ 30 ].

Responsibility of author

Authorship is not just a list of names. It is the matter of pride that has to be deserved, earned, and declared [ 15 ]. To maintain the integrity and credibility of medical research and to nourish the trust of public in scientific endeavors, all authors must follow the rules of good scientific publication practice and should stick to the following responsibilities (Table ​ (Table1 1 ):

• Do not fabricate or manipulate the data
• Avoid plagiarism and give proper acknowledgment to other works
• Decide the order of authorship prior to writing the paper to avoid future conflicts
• Declare whether research work has been published or presented before
• Declare COI
• Avoid ghost/gift/guest authorship
• Do not submit the manuscript to more than one journal for simultaneous consideration
• Take approval from the Institutional Ethics Committee before conducting research
• Last but not the least, take direct responsibility for appropriate portions of the content.

Role and responsibilities of author

COI conflict of interest, CONSORT Consolidated Standards of Reporting Trials, ARRIVE Animal research: reporting in vivo experiments, CTRI Clinical Trials Registry - India

Awareness of good publication practices should be generated among novice authors to prevent unethical practices in publication of scientific research. Each institute or department should resort to COPE or ICMJE recommendations for publications and draft their own SOP for authors who are actively involved in research. Unethical practices on the part of the authors or scientific misconduct should be discouraged and addressed by appropriate training and guidance.

Compliance with ethical standards

SS, and BSK declare that they have no conflict of interest.

The authors are solely responsible for the data and the contents of the paper. In no way, the Honorary Editor-in-Chief, Editorial Board Members, the Indian Society of Gastroenterology or the printer/publishers are responsible for the results/findings and content of this article.

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Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Home » Research Paper – Structure, Examples and Writing Guide

Research Paper – Structure, Examples and Writing Guide

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Research Paper

Definition:

Research Paper is a written document that presents the author’s original research, analysis, and interpretation of a specific topic or issue.

It is typically based on Empirical Evidence, and may involve qualitative or quantitative research methods, or a combination of both. The purpose of a research paper is to contribute new knowledge or insights to a particular field of study, and to demonstrate the author’s understanding of the existing literature and theories related to the topic.

Structure of Research Paper

The structure of a research paper typically follows a standard format, consisting of several sections that convey specific information about the research study. The following is a detailed explanation of the structure of a research paper:

The title page contains the title of the paper, the name(s) of the author(s), and the affiliation(s) of the author(s). It also includes the date of submission and possibly, the name of the journal or conference where the paper is to be published.

The abstract is a brief summary of the research paper, typically ranging from 100 to 250 words. It should include the research question, the methods used, the key findings, and the implications of the results. The abstract should be written in a concise and clear manner to allow readers to quickly grasp the essence of the research.

Introduction

The introduction section of a research paper provides background information about the research problem, the research question, and the research objectives. It also outlines the significance of the research, the research gap that it aims to fill, and the approach taken to address the research question. Finally, the introduction section ends with a clear statement of the research hypothesis or research question.

Literature Review

The literature review section of a research paper provides an overview of the existing literature on the topic of study. It includes a critical analysis and synthesis of the literature, highlighting the key concepts, themes, and debates. The literature review should also demonstrate the research gap and how the current study seeks to address it.

The methods section of a research paper describes the research design, the sample selection, the data collection and analysis procedures, and the statistical methods used to analyze the data. This section should provide sufficient detail for other researchers to replicate the study.

The results section presents the findings of the research, using tables, graphs, and figures to illustrate the data. The findings should be presented in a clear and concise manner, with reference to the research question and hypothesis.

The discussion section of a research paper interprets the findings and discusses their implications for the research question, the literature review, and the field of study. It should also address the limitations of the study and suggest future research directions.

The conclusion section summarizes the main findings of the study, restates the research question and hypothesis, and provides a final reflection on the significance of the research.

The references section provides a list of all the sources cited in the paper, following a specific citation style such as APA, MLA or Chicago.

How to Write Research Paper

You can write Research Paper by the following guide:

• Choose a Topic: The first step is to select a topic that interests you and is relevant to your field of study. Brainstorm ideas and narrow down to a research question that is specific and researchable.
• Conduct a Literature Review: The literature review helps you identify the gap in the existing research and provides a basis for your research question. It also helps you to develop a theoretical framework and research hypothesis.
• Develop a Thesis Statement : The thesis statement is the main argument of your research paper. It should be clear, concise and specific to your research question.
• Plan your Research: Develop a research plan that outlines the methods, data sources, and data analysis procedures. This will help you to collect and analyze data effectively.
• Collect and Analyze Data: Collect data using various methods such as surveys, interviews, observations, or experiments. Analyze data using statistical tools or other qualitative methods.
• Organize your Paper : Organize your paper into sections such as Introduction, Literature Review, Methods, Results, Discussion, and Conclusion. Ensure that each section is coherent and follows a logical flow.
• Write your Paper : Start by writing the introduction, followed by the literature review, methods, results, discussion, and conclusion. Ensure that your writing is clear, concise, and follows the required formatting and citation styles.
• Edit and Proofread your Paper: Review your paper for grammar and spelling errors, and ensure that it is well-structured and easy to read. Ask someone else to review your paper to get feedback and suggestions for improvement.
• Cite your Sources: Ensure that you properly cite all sources used in your research paper. This is essential for giving credit to the original authors and avoiding plagiarism.

Research Paper Example

Note : The below example research paper is for illustrative purposes only and is not an actual research paper. Actual research papers may have different structures, contents, and formats depending on the field of study, research question, data collection and analysis methods, and other factors. Students should always consult with their professors or supervisors for specific guidelines and expectations for their research papers.

Research Paper Example sample for Students:

Title: The Impact of Social Media on Mental Health among Young Adults

Abstract: This study aims to investigate the impact of social media use on the mental health of young adults. A literature review was conducted to examine the existing research on the topic. A survey was then administered to 200 university students to collect data on their social media use, mental health status, and perceived impact of social media on their mental health. The results showed that social media use is positively associated with depression, anxiety, and stress. The study also found that social comparison, cyberbullying, and FOMO (Fear of Missing Out) are significant predictors of mental health problems among young adults.

Introduction: Social media has become an integral part of modern life, particularly among young adults. While social media has many benefits, including increased communication and social connectivity, it has also been associated with negative outcomes, such as addiction, cyberbullying, and mental health problems. This study aims to investigate the impact of social media use on the mental health of young adults.

Literature Review: The literature review highlights the existing research on the impact of social media use on mental health. The review shows that social media use is associated with depression, anxiety, stress, and other mental health problems. The review also identifies the factors that contribute to the negative impact of social media, including social comparison, cyberbullying, and FOMO.

Methods : A survey was administered to 200 university students to collect data on their social media use, mental health status, and perceived impact of social media on their mental health. The survey included questions on social media use, mental health status (measured using the DASS-21), and perceived impact of social media on their mental health. Data were analyzed using descriptive statistics and regression analysis.

Results : The results showed that social media use is positively associated with depression, anxiety, and stress. The study also found that social comparison, cyberbullying, and FOMO are significant predictors of mental health problems among young adults.

Discussion : The study’s findings suggest that social media use has a negative impact on the mental health of young adults. The study highlights the need for interventions that address the factors contributing to the negative impact of social media, such as social comparison, cyberbullying, and FOMO.

Conclusion : In conclusion, social media use has a significant impact on the mental health of young adults. The study’s findings underscore the need for interventions that promote healthy social media use and address the negative outcomes associated with social media use. Future research can explore the effectiveness of interventions aimed at reducing the negative impact of social media on mental health. Additionally, longitudinal studies can investigate the long-term effects of social media use on mental health.

Limitations : The study has some limitations, including the use of self-report measures and a cross-sectional design. The use of self-report measures may result in biased responses, and a cross-sectional design limits the ability to establish causality.

Implications: The study’s findings have implications for mental health professionals, educators, and policymakers. Mental health professionals can use the findings to develop interventions that address the negative impact of social media use on mental health. Educators can incorporate social media literacy into their curriculum to promote healthy social media use among young adults. Policymakers can use the findings to develop policies that protect young adults from the negative outcomes associated with social media use.

References :

• Twenge, J. M., & Campbell, W. K. (2019). Associations between screen time and lower psychological well-being among children and adolescents: Evidence from a population-based study. Preventive medicine reports, 15, 100918.
• Primack, B. A., Shensa, A., Escobar-Viera, C. G., Barrett, E. L., Sidani, J. E., Colditz, J. B., … & James, A. E. (2017). Use of multiple social media platforms and symptoms of depression and anxiety: A nationally-representative study among US young adults. Computers in Human Behavior, 69, 1-9.
• Van der Meer, T. G., & Verhoeven, J. W. (2017). Social media and its impact on academic performance of students. Journal of Information Technology Education: Research, 16, 383-398.

Appendix : The survey used in this study is provided below.

Social Media and Mental Health Survey

• How often do you use social media per day?
• Less than 30 minutes
• 30 minutes to 1 hour
• 1 to 2 hours
• 2 to 4 hours
• More than 4 hours
• Which social media platforms do you use?
• Others (Please specify)
• How often do you experience the following on social media?
• Social comparison (comparing yourself to others)
• Cyberbullying
• Fear of Missing Out (FOMO)
• Have you ever experienced any of the following mental health problems in the past month?
• Do you think social media use has a positive or negative impact on your mental health?
• Very positive
• Somewhat positive
• Somewhat negative
• Very negative
• In your opinion, which factors contribute to the negative impact of social media on mental health?
• Social comparison
• In your opinion, what interventions could be effective in reducing the negative impact of social media on mental health?
• Education on healthy social media use
• Counseling for mental health problems caused by social media
• Social media detox programs
• Regulation of social media use

Thank you for your participation!

Applications of Research Paper

Research papers have several applications in various fields, including:

• Advancing knowledge: Research papers contribute to the advancement of knowledge by generating new insights, theories, and findings that can inform future research and practice. They help to answer important questions, clarify existing knowledge, and identify areas that require further investigation.
• Informing policy: Research papers can inform policy decisions by providing evidence-based recommendations for policymakers. They can help to identify gaps in current policies, evaluate the effectiveness of interventions, and inform the development of new policies and regulations.
• Improving practice: Research papers can improve practice by providing evidence-based guidance for professionals in various fields, including medicine, education, business, and psychology. They can inform the development of best practices, guidelines, and standards of care that can improve outcomes for individuals and organizations.
• Educating students : Research papers are often used as teaching tools in universities and colleges to educate students about research methods, data analysis, and academic writing. They help students to develop critical thinking skills, research skills, and communication skills that are essential for success in many careers.
• Fostering collaboration: Research papers can foster collaboration among researchers, practitioners, and policymakers by providing a platform for sharing knowledge and ideas. They can facilitate interdisciplinary collaborations and partnerships that can lead to innovative solutions to complex problems.

When to Write Research Paper

Research papers are typically written when a person has completed a research project or when they have conducted a study and have obtained data or findings that they want to share with the academic or professional community. Research papers are usually written in academic settings, such as universities, but they can also be written in professional settings, such as research organizations, government agencies, or private companies.

Here are some common situations where a person might need to write a research paper:

• For academic purposes: Students in universities and colleges are often required to write research papers as part of their coursework, particularly in the social sciences, natural sciences, and humanities. Writing research papers helps students to develop research skills, critical thinking skills, and academic writing skills.
• For publication: Researchers often write research papers to publish their findings in academic journals or to present their work at academic conferences. Publishing research papers is an important way to disseminate research findings to the academic community and to establish oneself as an expert in a particular field.
• To inform policy or practice : Researchers may write research papers to inform policy decisions or to improve practice in various fields. Research findings can be used to inform the development of policies, guidelines, and best practices that can improve outcomes for individuals and organizations.
• To share new insights or ideas: Researchers may write research papers to share new insights or ideas with the academic or professional community. They may present new theories, propose new research methods, or challenge existing paradigms in their field.

Purpose of Research Paper

The purpose of a research paper is to present the results of a study or investigation in a clear, concise, and structured manner. Research papers are written to communicate new knowledge, ideas, or findings to a specific audience, such as researchers, scholars, practitioners, or policymakers. The primary purposes of a research paper are:

• To contribute to the body of knowledge : Research papers aim to add new knowledge or insights to a particular field or discipline. They do this by reporting the results of empirical studies, reviewing and synthesizing existing literature, proposing new theories, or providing new perspectives on a topic.
• To inform or persuade: Research papers are written to inform or persuade the reader about a particular issue, topic, or phenomenon. They present evidence and arguments to support their claims and seek to persuade the reader of the validity of their findings or recommendations.
• To advance the field: Research papers seek to advance the field or discipline by identifying gaps in knowledge, proposing new research questions or approaches, or challenging existing assumptions or paradigms. They aim to contribute to ongoing debates and discussions within a field and to stimulate further research and inquiry.
• To demonstrate research skills: Research papers demonstrate the author’s research skills, including their ability to design and conduct a study, collect and analyze data, and interpret and communicate findings. They also demonstrate the author’s ability to critically evaluate existing literature, synthesize information from multiple sources, and write in a clear and structured manner.

Characteristics of Research Paper

Research papers have several characteristics that distinguish them from other forms of academic or professional writing. Here are some common characteristics of research papers:

• Evidence-based: Research papers are based on empirical evidence, which is collected through rigorous research methods such as experiments, surveys, observations, or interviews. They rely on objective data and facts to support their claims and conclusions.
• Structured and organized: Research papers have a clear and logical structure, with sections such as introduction, literature review, methods, results, discussion, and conclusion. They are organized in a way that helps the reader to follow the argument and understand the findings.
• Formal and objective: Research papers are written in a formal and objective tone, with an emphasis on clarity, precision, and accuracy. They avoid subjective language or personal opinions and instead rely on objective data and analysis to support their arguments.
• Citations and references: Research papers include citations and references to acknowledge the sources of information and ideas used in the paper. They use a specific citation style, such as APA, MLA, or Chicago, to ensure consistency and accuracy.
• Peer-reviewed: Research papers are often peer-reviewed, which means they are evaluated by other experts in the field before they are published. Peer-review ensures that the research is of high quality, meets ethical standards, and contributes to the advancement of knowledge in the field.
• Objective and unbiased: Research papers strive to be objective and unbiased in their presentation of the findings. They avoid personal biases or preconceptions and instead rely on the data and analysis to draw conclusions.

Advantages of Research Paper

Research papers have many advantages, both for the individual researcher and for the broader academic and professional community. Here are some advantages of research papers:

• Contribution to knowledge: Research papers contribute to the body of knowledge in a particular field or discipline. They add new information, insights, and perspectives to existing literature and help advance the understanding of a particular phenomenon or issue.
• Opportunity for intellectual growth: Research papers provide an opportunity for intellectual growth for the researcher. They require critical thinking, problem-solving, and creativity, which can help develop the researcher’s skills and knowledge.
• Career advancement: Research papers can help advance the researcher’s career by demonstrating their expertise and contributions to the field. They can also lead to new research opportunities, collaborations, and funding.
• Academic recognition: Research papers can lead to academic recognition in the form of awards, grants, or invitations to speak at conferences or events. They can also contribute to the researcher’s reputation and standing in the field.
• Impact on policy and practice: Research papers can have a significant impact on policy and practice. They can inform policy decisions, guide practice, and lead to changes in laws, regulations, or procedures.
• Advancement of society: Research papers can contribute to the advancement of society by addressing important issues, identifying solutions to problems, and promoting social justice and equality.

Limitations of Research Paper

Research papers also have some limitations that should be considered when interpreting their findings or implications. Here are some common limitations of research papers:

• Limited generalizability: Research findings may not be generalizable to other populations, settings, or contexts. Studies often use specific samples or conditions that may not reflect the broader population or real-world situations.
• Potential for bias : Research papers may be biased due to factors such as sample selection, measurement errors, or researcher biases. It is important to evaluate the quality of the research design and methods used to ensure that the findings are valid and reliable.
• Ethical concerns: Research papers may raise ethical concerns, such as the use of vulnerable populations or invasive procedures. Researchers must adhere to ethical guidelines and obtain informed consent from participants to ensure that the research is conducted in a responsible and respectful manner.
• Limitations of methodology: Research papers may be limited by the methodology used to collect and analyze data. For example, certain research methods may not capture the complexity or nuance of a particular phenomenon, or may not be appropriate for certain research questions.
• Publication bias: Research papers may be subject to publication bias, where positive or significant findings are more likely to be published than negative or non-significant findings. This can skew the overall findings of a particular area of research.
• Time and resource constraints: Research papers may be limited by time and resource constraints, which can affect the quality and scope of the research. Researchers may not have access to certain data or resources, or may be unable to conduct long-term studies due to practical limitations.

About the author

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Researcher, Academic Writer, Web developer

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What is a Corresponding Author?

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Are you familiar with the terms “corresponding author” and “first author,” but you don’t know what they really mean? This is a common doubt, especially at the beginning of a researcher’s career, but easy to explain: fundamentally, a corresponding author takes the lead in the manuscript submission for publication process, whereas the first author is actually the one who did the research and wrote the manuscript.

The order of the authors can be arranged in whatever order suits the research group best, but submissions must be made by the corresponding author. It can also be the case that you don’t belong in a research group, and you want to publish your own paper independently, so you will probably be the corresponding author and first author at the same time.

Corresponding author meaning:

The corresponding author is the one individual who takes primary responsibility for communication with the journal during the manuscript submission, peer review, and publication process. Normally, he or she also ensures that all the journal’s administrative requirements, such as providing details of authorship, ethics committee approval, clinical trial registration documentation, and gathering conflict of interest forms and statements, are properly completed, although these duties may be delegated to one or more co-authors.

Generally, corresponding authors are senior researchers or group leaders with some – or a lot of experience – in the submission and publishing process of scientific research. They are someone who has not only contributed to the paper significantly but also has the ability to ensure that it goes through the publication process smoothly and successfully.

What is a corresponding author supposed to do?

A corresponding author is responsible for several critical aspects at each stage of a study’s dissemination – before and after publication.

If you are a corresponding author for the first time, take a look at these 6 simple tips that will help you succeed in this important task:

• Ensure that major deadlines are met
• Prepare a submission-ready manuscript
• Put together a submission package
• Get all author details correct
• Ensure ethical practices are followed
• Take the lead on open access

In short, the corresponding author is the one responsible for bringing research (and researchers) to the eyes of the public. To be successful, and because the researchers’ reputation is also at stake, corresponding authors always need to remember that a fine quality text is the first step to impress a team of peers or even a more refined audience. Elsevier’s team of language and translation professionals is always ready to perform text editing services that will provide the best possible material to go forward with a submission or/and a publication process confidently.

Who is the first author of a scientific paper?

The first author is usually the person who made the most significant intellectual contribution to the work. That includes designing the study, acquiring and analyzing data from experiments and writing the actual manuscript. As a first author, you will have to impress a vast group of players in the submission and publication processes. But, first of all, if you are in a research group, you will have to catch the corresponding author’s eye. The best way to give your work the attention it deserves, and the confidence you expect from your corresponding author, is to deliver a flawless manuscript, both in terms of scientific accuracy and grammar.

If you are not sure about the written quality of your manuscript, and you feel your career might depend on it, take full advantage of Elsevier’s professional text editing services. They can make a real difference in your work’s acceptance at each stage, before it comes out to the public.

Language Editing Services by Elsevier Author Services:

Through our Language Editing Services , we correct proofreading errors, and check for grammar and syntax to make sure your paper sounds natural and professional. We also make sure that editors and reviewers can understand the science behind your manuscript.

With more than a hundred years of experience in publishing, Elsevier is trusted by millions of authors around the world.

Check our video Elsevier Author Services – Language Editing to learn more about Author Services.

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Office of the Provost

Guidance on authorship in scholarly or scientific publications, general principles.

The public’s trust in and benefit from academic research and scholarship relies upon all those involved in the scholarly endeavor adhering to the highest ethical standards, including standards related to publication and dissemination of findings and conclusions.

Accordingly, all scholarly or scientific publications involving faculty, staff, students and/or trainees arising from academic activities performed under the auspices of Yale University must include appropriate attribution of authorship and disclosure of relevant affiliations of those involved in the work, as described below.

These publications, which, for the purposes of this guidance, include articles, abstracts, manuscripts submitted for publication, presentations at professional meetings, and applications for funding, must appropriately acknowledge contributions of colleagues involved in the design, conduct or dissemination of the work by neither overly attributing contribution nor ignoring meaningful contributions.

Financial and other supporting relationships of those involved in the scholarly work must be transparent and disclosed in publications arising from the work.

Authorship Standards

Authorship of a scientific or scholarly paper should be limited to those individuals who have contributed in a meaningful and substantive way to its intellectual content. All authors are responsible for fairly evaluating their roles in the project as well as the roles of their co-authors to ensure that authorship is attributed according to these standards in all publications for which they will be listed as an author.

Requirement for Attribution of Authorship

Each author should have participated sufficiently in the work to take public responsibility for its content. All co-authors should have been directly involved in all three of the following:

• planning and contribution to some component (conception, design, conduct, analysis, or interpretation) of the work which led to the paper or interpreting at least a portion of the results;
• writing a draft of the article or revising it for intellectual content; and
• final approval of the version to be published.  All authors should review and approve the manuscript before it is submitted for publication, at least as it pertains to their roles in the project.

Some diversity exists across academic disciplines regarding acceptable standards for substantive contributions that would lead to attribution of authorship. This guidance is intended to allow for such variation to disciplinary best practices while ensuring authorship is not inappropriately assigned.

Lead Author

The first author is usually the person who has performed the central experiments of the project. Often, this individual is also the person who has prepared the first draft of the manuscript. The lead author is ultimately responsible for ensuring that all other authors meet the requirements for authorship as well as ensuring the integrity of the work itself. The lead author will usually serve as the corresponding author.

Co-Author(s)

Each co-author is responsible for considering his or her role in the project and whether that role merits attribution of authorship. Co-authors should review and approve the manuscript, at least as it pertains to their roles in the project.

External Collaborators, Including Sponsor or Industry Representatives

Individuals who meet the criteria for authorship should be included as authors irrespective of their institutional affiliations. In general, the use of “ghostwriters” is prohibited, i.e., individuals who have contributed significant portions of the text should be named as authors or acknowledged in the final publication. Industry representatives or others retained by industry who contribute to an article and meet the requirements for authorship or acknowledgement must be appropriately listed as contributors or authors on the article and their industry affiliation must be disclosed in the published article.

Acknowledgements

Individuals who do not meet the requirements for authorship but who have provided a valuable contribution to the work should be acknowledged for their contributing role as appropriate to the publication.

Courtesy or Gift Authorship

Individuals do not satisfy the criteria for authorship merely because they have made possible the conduct of the research and/or the preparation of the manuscript. Under no circumstance should individuals be added as co-authors based on the individual’s stature as an attempt to increase the likelihood of publication or credibility of the work. For example, heading a laboratory, research program, section, or department where the research takes place does not, by itself, warrant co-authorship of a scholarly paper. Nor should “gift” co-authorship be conferred on those whose only contributions have been to provide, for example, routine technical services, to refer patients or participants for a study, to provide a valuable reagent, to assist with data collection and assembly, or to review a completed manuscript for suggestions. Although not qualifying as co-authors, individuals who assist the research effort may warrant appropriate acknowledgement in the completed paper.

Senior faculty members should be named as co-authors on work independently generated by their junior colleagues only if they have made substantial intellectual contributions to the experimental design, interpretation of findings and manuscript preparation.

Authorship Disputes

Determinations of authorship roles are often complex, delicate and potentially controversial. To avoid confusion and conflict, discussion of attribution should be initiated early in the development of any collaborative publication. For disputes that cannot be resolved amicably, individuals may seek the guidance of the dean of their school or the cognizant deputy provost in the Faculty of Arts & Sciences.

Disclosure of Research Funding and Other Support

In all scientific and scholarly publications and all manuscripts submitted for publication, authors should acknowledge the sources of support for all activities leading to and facilitating preparation of the publication or manuscript, including, but not limited to:

• grant, contract, and gift support;
• salary support if other than institutional funds. Note that salary support that is provided to the University by an external entity does not constitute institutional funds by virtue of being distributed by the University; and
• technical or other support if substantive and meaningful to the completion of the project.

Disclosure of Financial Interests and External Activities

Authors should fully disclose related financial interests and outside activities in publications (including articles, abstracts, manuscripts submitted for publication), presentations at professional meetings, and applications for funding.

In addition, authors should comply with the disclosure requirements of the University’s Committee on Conflict of Interest.

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What does "author title" mean in a manuscript submission system?

What does the author title mean in a manuscript application form? Does it mean {professor- assistant professor- lecturer} and if he/she isn't a university's staff what would the title be? Presuming he/she is master degree student in a medical specialty?

• 1 I don't know what a manuscript application form is specifically, but I would assume that if you don't hold a professional title, your title is simply Mr/Mrs/Ms etc. –  astronat supports the strike Commented Nov 13, 2016 at 0:18
• the author's title when writing a research, medical paper or an article –  Aalaa Elsadek Commented Nov 13, 2016 at 0:24
• 8 Then I think you've answered your own question. As I said, if you don't hold a particular title (Professor, Doctor, Lord, Reverend, Captain, or whatever it may be) then your title is Mr/Mrs/Ms etc. As far as I know, a Masters degree doesn't confer any pre-nominal titles. –  astronat supports the strike Commented Nov 13, 2016 at 0:28

If the author does not hold any of the usual academic tiles such as Dr/Prof./Asst. Prof. the status quo defaults to Mr/Ms/Mrs.

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A timeless resource: BGSU organizational change management research still highly sought after

Estimated Reading Time:  

The article “Organizational Diagnosis: An Evidence-Based Approach” has been read more than 58,000 times

#1 University in Ohio for Student Experience

Innovative engineering degrees, #1 public university in the midwest students would choose again for the fourth consecutive year.

More than a decade after an article on organizational change management authored by current and retired Bowling Green State University faculty members was published, its groundbreaking research continues to draw interest.

According to ResearchGate, the “Organizational Diagnosis: An Evidence-Based Approach” article has been read more than 58,000 times since its publication in 2012. It is the most frequently read article from BGSU accessed through its site.

“Often in management, there’s a focus on results,” said Dr. James McFillen, an emeritus BGSU business professor and the paper’s lead author. “It intends to be results-oriented rather than cause-oriented. To fix something, you first have to know what is wrong.”

The article's origins date back to the early days of the BGSU Executive Master of Organization Development program, established in 1974 by Dr. Glenn Varney, an emeritus business professor and co-author alongside McFillen; Dr. Deborah A. O’Neil, a professor of management and director of the master’s program; and Dr. William Balzer, emeritus psychology professor.

The program, housed in the Allen W. and Carol M. Schmidthorst College of Business , was the first in Ohio and third in the nation and has been widely recognized for excellence.

Following Varney’s tenure as the program’s director, McFillen led the organization development master's program for more than 15 years, beginning in 1994. He focused on the scientific side of organizational behavior, sparking the work that resulted in the Journal of Change Management article that has drawn interest from various disciplines.

“I decided that if I was going to be involved, it needed to be a scientifically based, research-driven program,” McFillen said. “Over time, I reworked the curriculum to give it a more behavioral science orientation to explain how organizations function and how you could change them.”

During the process of shifting the program’s focus to research, McFillen realized a vital piece was missing — the diagnostic process of determining causes of problems within an organization. He said existing organization development literature offered information on fixing problems but didn’t explain the process of diagnosing them.

“You had all these people writing articles about their favorite things to do to improve organizations, but there was no science behind it,” he said.

To find a solution, McFillen and his colleagues reviewed disciplines that used a diagnostic process to analyze problems, narrowing it down to engineering and medicine. While engineering uses a scientific method to diagnose issues, the process doesn’t account for human behavior. Consequently, they concluded the medical diagnosis model was better suited to organization development.

Using a medical model, the BGSU faculty members developed the concept of organizational diagnosis as the key step toward effective change and have successfully used it in many situations. They developed a rigorous process to correctly identify “symptoms” of problems plaguing an organization.

“The article continually finds a new audience,” Varney said. “If you are going to make a change in an organization, you need to use a very systematic way of doing it. Otherwise, it will backfire on you every single time. Organizations are going through tremendous change these days, and that’s why I think they are still reading our article now.”

First presented in the 2012 article, McFillen and Varney’s methods were later conveyed in a book they co-authored with Scott Janoch, “Grasp the Situation: Lessons Learned in Change Leadership,” which presents the organizational diagnosis process through lively stories from the authors’ experiences.

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• Published: 05 January 2024

Enhancing geometric representations for molecules with equivariant vector-scalar interactive message passing

• Yusong Wang 1 , 2   na1 ,
• Tong Wang   ORCID: orcid.org/0000-0002-9483-0050 1   na1 ,
• Shaoning Li 1   na1 ,
• Xinheng He 1 , 3 , 4 ,
• Mingyu Li 1 , 5 ,
• Zun Wang   ORCID: orcid.org/0000-0002-8763-8327 1 ,
• Nanning Zheng 2 ,
• Bin Shao   ORCID: orcid.org/0000-0002-9790-5687 1 &
• Tie-Yan Liu   ORCID: orcid.org/0000-0002-0476-8020 1  

Nature Communications volume  15 , Article number:  313 ( 2024 ) Cite this article

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• Chemical biology
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• Protein structure predictions

Geometric deep learning has been revolutionizing the molecular modeling field. Despite the state-of-the-art neural network models are approaching ab initio accuracy for molecular property prediction, their applications, such as drug discovery and molecular dynamics (MD) simulation, have been hindered by insufficient utilization of geometric information and high computational costs. Here we propose an equivariant geometry-enhanced graph neural network called ViSNet, which elegantly extracts geometric features and efficiently models molecular structures with low computational costs. Our proposed ViSNet outperforms state-of-the-art approaches on multiple MD benchmarks, including MD17, revised MD17 and MD22, and achieves excellent chemical property prediction on QM9 and Molecule3D datasets. Furthermore, through a series of simulations and case studies, ViSNet can efficiently explore the conformational space and provide reasonable interpretability to map geometric representations to molecular structures.

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Introduction.

Molecular modeling plays a crucial role in modern scientific and engineering fields, aiding in the understanding of chemical reactions, facilitating new drug development, and driving scientific and technological advancements 1 , 2 , 3 , 4 . One commonly used method in molecular modeling is density functional theory (DFT). DFT enables accurate calculations of energy, forces, and other chemical properties of molecules 5 , 6 . However, due to the large computational requirements, DFT calculations often demand significant computational resources and time, particularly for large molecular systems or high-precision calculations. Machine learning (ML) offers an alternative solution by learning from reference data with ab initio accuracy and high computational efficiency 7 , 8 . Gradient-domain machine learning (GDML) 9 constructs accurate molecular force fields using conservation of energy and limited samples from ab initio molecular dynamics trajectories, enabling cost-effective simulations while maintaining accuracy. Symmetric GDML (sGDML) 10 further improves force field construction by incorporating physical symmetries, achieving CCSD(T)-level accuracy for flexible molecules. An exact iterative approach (Global sGDML) 11 extends sGDML to global force fields for molecules with several hundred atoms, maintaining correlations of atomic degree and accurately describing complex molecules and materials. In recent years, deep learning (DL) has demonstrated its powerful ability to learn from raw data without any hand-crafted features in many fields and thus attracted more and more attention. However, the inherent drawback of deep learning, which requires large amounts of data, has become a bottleneck for its application to more scenarios 12 . To alleviate the dependency on data for DL potentials, recent works have incorporated the inductive bias of symmetry into neural network design, known as geometric deep learning (GDL). Symmetry describes the conservation of physical laws, i.e., the unchanged physical properties with any transformations such as translations or rotations. It allows GDL to be extended to limited data scenarios without any data augmentation.

Equivariant graph neural network (EGNN) is one of the representative approaches in GDL, which has extensive capability to model molecular geometry 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 . A popular kind of EGNN conducts equivariance from directional information and involves geometric features to predict molecular properties. GemNet 20 extends the invariant DimeNet/DimeNet++ 16 , 17 with dihedral information. They explicitly extract geometric information in the Euclidean space with first-order geometric tensor, i.e., setting l max  = 1. PaiNN 18 and equivariant transformer 19 further adopt vector embedding and scalarize the angular representation implicitly via the inner product of the vector embedding itself. They reduce the complexity of explicit geometry extraction by taking the angular information into consideration. Another mainstream approach to achieving equivariance is through group representation theory, which can achieve higher accuracy but comes with large computational costs. NequIP, Allegro, and MACE 12 , 22 , 23 achieve state-of-the-art performance on several molecular dynamics simulation datasets leveraging high-order geometric tensors. On the one hand, algorithms based on group representation theory have strong mathematical foundations and are able to fully utilize geometric information using high-order geometric tensors. On the other hand, these algorithms often require computationally expensive operations such as the Clebsch–Gordan product (CG-product) 24 , making them possibly suitable for periodic systems with elaborate model design but impractical for large molecular systems such as chemical and biological molecules without periodic boundary conditions.

In this study, we propose ViSNet (short for “Vector-Scalar interactive graph neural Network"), which alleviates the dilemma between computational costs and sufficient utilization of geometric information. By incorporating an elaborate runtime geometry calculation (RGC) strategy, ViSNet implicitly extracts various geometric features, i.e., angles, dihedral torsion angles, and improper angles in accordance with the force field of classical MD with linear time complexity, thus significantly accelerating model training and inference while reducing the memory consumption. To extend the vector representation, we introduce spherical harmonics and simplify the computationally expensive Clebsch–Gordan product with the inner product. Furthermore, we present a well-designed vector–scalar interactive equivariant message passing (ViS-MP) mechanism, which fully utilizes the geometric features by interacting vector hidden representations with scalar ones. When comprehensively evaluated on some benchmark datasets, ViSNet outperforms all state-of-the-art algorithms on all molecules in MD17, revised MD17 and MD22 datasets and shows superior performance on QM9, Molecule3D dataset indicating the powerful capability of molecular geometric representation. ViSNet also has won the PCQM4Mv2 track in the OGB-LCS@NeurIPS2022 competition ( https://ogb.stanford.edu/neurips2022/results/ ). We then performed molecular dynamics simulations for each molecule on MD17 driven by ViSNet trained only with limited data (950 samples). The highly consistent interatomic distance distributions and the explored potential energy surfaces between ViSNet and quantum simulation illustrate that ViSNet is genuinely data-efficient and can perform simulations with high fidelity. To further explore the usefulness of ViSNet to real-world applications, we used an in-house dataset that consists of about 10,000 different conformations of the 166-atom mini-protein Chignolin derived from replica exchange molecular dynamics and calculated at the DFT level. When evaluated on the dataset, ViSNet also achieved significantly better performance than empirical force fields, and the simulations performed by ViSNet exhibited very close force calculation to DFT. In addition, ViSNet exhibits reasonable interpretability to map geometric representation to molecular structures. The contributions of ViSNet can be summarized as follows:

Proposing an RGC module that utilizes high-order geometric tensors to implicitly extract various geometric features, including angles, dihedral torsion angles, and improper angles, with linear time complexity.

Introducing ViS-MP mechanism to enable efficient interaction between vector hidden representations and scalar ones and fully exploit the geometric information.

Achieving state-of-the-art performance in six benchmarks for predicting energy, forces, HOMO-LUMO gap, and other quantum properties of molecules.

Performing molecular dynamics simulations driven by ViSNet on both small molecules and 166-atom Chignolin with high fidelity.

Demonstrating reasonable model interpretability between geometric features and molecular structures.

Overview of ViSNet

ViSNet is a versatile EGNN that predicts potential energy, atomic forces as well as various quantum chemical properties by taking atomic coordinates and numbers as inputs. As shown in Fig.  1 a, the model is composed of an embedding block and multiple stacked ViSNet blocks, followed by an output block. The atomic number and coordinates are fed into the embedding block followed by ViSNet blocks to extract and encode geometric representations. The geometric representations are then used to predict molecular properties through the output block. It is worth noting that ViSNet is an energy-conserving potential, i.e., the predicted atomic forces are derived from the negative gradients of the potential energy with respect to the coordinates 9 , 10 .

a Model sketch of ViSNet. ViSNet embeds the 3D structures of molecules and extracts the geometric information through a series of ViSNet blocks and outputs the molecule properties such as energy, forces, and HOMO–LUMO gap through an output block. b Flowchart of one ViSNet Block. One ViSNet block consists of two modules: (i) Scalar2Vec , responsible for attaching scalar embeddings to vectors.; (ii) Vec2Scalar , renovates scalar embeddings built on RGC strategy. The inputs of Scalar2Vec are the node embedding h i , edge embedding f i j , direction unit \({\overrightarrow{v}}_{i}\) and the relative positions between two atoms. The edge-fusion graph attention module (serves as \({\phi }_{{\rm {m}}}^{{\rm {s}}}\) ) takes as input h i and the output of the dense layer following f i j , and outputs scalar messages. Before aggregation, each scalar message is transformed through a dense layer, and then fused with the unit of the relative position \({\overrightarrow{u}}_{ij}\) and its own direction unit \({\overrightarrow{v}}_{j}\) . We further compute the vector messages and aggregate them all among the neighborhood. Through a gated residual connection, the final residual \({{\Delta }}{\overrightarrow{v}}_{i}\) is produced. In Vec2Scalar module, by Hadamard production of aggregated scalar messages and the output of RGC-Angle calculation and adding a gated residual connection, the final Δ h i is figured out. Likewise, combining the projected f i j and the output of RGC-Dihedral calculation, the final Δ f i j is determined.

The success of classical force fields shows that geometric features such as interatomic distances, angles, dihedral torsion angles, and improper angles in Fig.  2 are essential to determine the total potential energy of molecules. The explicit extraction of invariant geometric representations in previous studies often suffers from a large amount of time or memory consumption during model training and inference. Given an atom, the calculation of angular information scales \({{{{{{{\mathcal{O}}}}}}}}({{{{{{{{\mathcal{N}}}}}}}}}^{2})\) with the number of neighboring atoms, while the computational complexity is even \({{{{{{{\mathcal{O}}}}}}}}({{{{{{{{\mathcal{N}}}}}}}}}^{3})\) for dihedrals 20 . To alleviate this problem, inspired by Sch¨utt et al. 18 , we propose runtime geometry calculation (RGC), which uses an equivariant vector representation (termed as direction unit) for each node to preserve its geometric information. RGC directly calculates the geometric information from the direction unit which only sums the vectors from the target node to its neighbors once. Therefore, the computational complexity can be reduced to \({{{{{{{\mathcal{O}}}}}}}}({{{{{{{\mathcal{N}}}}}}}})\) . Notably, beyond employing angular information that has been used in PaiNN 18 and ET 19 , ViSNet further considers the dihedral torsion and improper angle calculation with higher geometric tensors.

The bonded terms consist of bond length, bond angle, dihedral torsion, and improper angle. The RGC module depicts all bonded terms of classical MD as model operations in linear time complexity. Yellow arrow \({\overrightarrow{v}}_{i}\) denotes the direction unit in Eq. ( 1 ).

Considering the sub-structure of a toy molecule with four atoms shown in Fig.  2 , the angular information of the target node i could be conducted from the vector \({\overrightarrow{r}}_{ij}\) as follows:

where \({\overrightarrow{r}}_{ij}\) is the vector from node i to its neighboring node j , \({\overrightarrow{u}}_{ij}\) is the unit vector of \({\overrightarrow{r}}_{ij}\) . Here, we define the direction unit \({\overrightarrow{v}}_{i}\) as the sum of all unit vectors from node i to its all neighboring nodes j , where node i is the intersection of all unit vectors. As shown in Eq. ( 2 ), we calculate the inner product of the direction unit \({\overrightarrow{v}}_{i}\) which represents the sum of the inner products of unit vectors from node i to all its neighboring nodes. Combining with Eq. ( 1 ), the inner product of direction \({\overrightarrow{v}}_{i}\) finally stands for the sum of cosine values of all angles formed by node i and any two of its neighboring nodes.

Similar to runtime angle calculation, we also calculate the vector rejection 25 of the direction unit \({\overrightarrow{v}}_{i}\) of node i and \({\overrightarrow{v}}_{j}\) of node j on the vector \({\overrightarrow{u}}_{ij}\) and \({\overrightarrow{u}}_{ji}\) , respectively.

where \({{{{{{{{\rm{Rej}}}}}}}}}_{\overrightarrow{b}}(\overrightarrow{a})\) represents the vector component of \(\overrightarrow{a}\) perpendicular to \(\overrightarrow{b}\) , termed as the vector rejection. \({\overrightarrow{u}}_{ij}\) and \({\overrightarrow{v}}_{i}\) are defined in Eq. ( 1 ). \({\overrightarrow{w}}_{ij}\) represents the sum of the vector rejection \({{{{{{{{\rm{Rej}}}}}}}}}_{{\overrightarrow{u}}_{ij}}({\overrightarrow{u}}_{im})\) and \({\overrightarrow{w}}_{ji}\) represents the sum of the vector rejection \({{{{{{{{\rm{Rej}}}}}}}}}_{{\overrightarrow{u}}_{ji}}({\overrightarrow{u}}_{jn})\) . The inner product between \({\overrightarrow{w}}_{ij}\) and \({\overrightarrow{w}}_{ji}\) is then calculated to conduct dihedral torsion angle information of the intersecting edge e i j as follows:

The improper angle is derived from a pyramid structure forming by 4 nodes. As the last toy molecule shown in Fig.  2 , node i is the vertex of the pyramid, and the improper torsion angle is formed by two adjacent planes with an intersecting edge e i j . We can also calculate the improper angle by vector rejection:

In the same way, the inner product between \({\overrightarrow{t}}_{ij}\) and \({\overrightarrow{t}}_{ji}\) indicates the summation of improper angle information formed by e i j :

Multiple works have shown the effectiveness of high-order geometric tensors for molecular modeling 12 , 22 , 26 , 27 . However, the computational overheads of these approaches are generally expansive due to the CG-product, impeding their further application for large systems. In this work, we convert the vectors to high-order representation with spherical harmonics but discard CG-product with the inner product following the idea of RGC. We find that the extended high-order geometric tensors can still represent the above angular information in the form of Legendre polynomials according to the addition theorem:

where the P l is the Legendre polynomial of degree l , Y l , m denotes the spherical harmonics function and \({Y}_{l,m}^{*}\) denotes its complex conjugation. We sum the product of different order l to obtain the scalar angular representation, which is the same operation as the inner product. It is worth noting that such an extension does not increase the model size and keeps the model architecture unchanged. We also provide proof about the rotational invariance of the RGC strategy in the section “Proofs of the rotational invariance of RGC ”.

In order to make full use of geometric information and enhance the interaction between scalars and vectors, we designed an effective vector–scalar interactive message-passing mechanism with respect to the intersecting nodes and edges for angles and dihedrals, respectively. It is important to note that previous studies 18 , 19 primarily focused on updating node features, whereas our approach updates both node and edge features during message passing, leading to a more comprehensive geometric representation. The key operations in ViS-MP are given as follows:

where h i denotes the scalar embedding of node i , f i j stands for the edge feature between node i and node j . \({\overrightarrow{v}}_{i}\) represents the embedding of the direction unit mentioned in RGC. The superscript of variables indicates the index of the block that the variables belong to. We omit the improper angle here for brevity. A comprehensive version is depicted in Supplementary. ViS-MP extends the conventional message passing, aggregation, and update processes with vector–scalar interactions. Eqs. ( 8 ) and ( 9 ) depict our message-passing and aggregation processes. To be concrete, scalar messages m i j incorporating scalar embedding h j , h i , and f i j are passed and then aggregated to node i through a message function \({\phi }_{m}^{s}\) (Eq. ( 8 )). Similar operations are applied for vector messages \({\overrightarrow{m}}_{i}^{l}\) of node i that incorporates scalar message m i j , vector \({\overrightarrow{r}}_{ij}\) and vector embedding \({\overrightarrow{v}}_{j}\) (Eq. ( 9 )). Equations ( 10 ) and ( 11 ) demonstrate the update processes. h i is updated by the aggregated scalar message output m i while the inner product of \({\overrightarrow{v}}_{i}\) is updated through an update function \({\phi }_{un}^{s}\) . Then \({\overrightarrow{f}}_{ij}\) is updated by the inner product of the rejection of the vector embedding \({\overrightarrow{v}}_{i}\) and \({\overrightarrow{v}}_{j}\) through an update function \({\phi }_{ue}^{s}\) . Finally, the vector embedding \({\overrightarrow{v}}_{i}\) is updated by both scalar and vector messages through an update function \({\phi }_{un}^{v}\) . Notably, the vectors update function, i.e., ϕ v require to be equivariant. The detailed message and update functions can be found in the Methods section. A proof about the equivariance of ViS-MP can be found in Supplementary Methods.

In summary, the geometric features are extracted by inner products in the RGC strategy and the scalar and vector embeddings are cyclically updating each other in ViS-MP so as to learn a comprehensive geometric representation from molecular structures.

Accurate quantum chemical property predictions

We evaluated ViSNet on several prevailing benchmark datasets including MD17 9 , 10 , 28 , revised MD17 29 , MD22 30 , QM9 31 , Molecule3D 32 , and OGB-LSC PCQM4Mv2 33 for energy, force, and other molecular property prediction. MD17 consists of the MD trajectories of seven small organic molecules; the number of conformations in each molecule dataset ranges from 133,700 to 993,237. The dataset rMD17 is a reproduced version of MD17 with higher accuracy. MD22 is a recently proposed MD trajectories dataset that presents challenges with respect to larger system sizes (42–370 atoms). Large molecules such as proteins, lipids, carbohydrates, nucleic acids, and supramolecules are included in MD22. QM9 consists of 12 kinds of quantum chemical properties of 133,385 small organic molecules with up to 9 heavy atoms. Molecule3D is a recently proposed dataset including 3,899,647 molecules collected from PubChemQC with their ground-state structures and corresponding properties calculated by DFT. We focus on the prediction of the HOMO–LUMO gap following ComENet 34 . OGB-LSC PCQM4Mv2 is a quantum chemistry dataset originally curated under the PubChemQC including a DFT-calculated HOMO–LUMO gap of 3,746,619 molecules. The 3D conformations are provided for 3,378,606 training molecules but not for the validation and test sets. The training details of ViSNet on each benchmark are described in the “Methods” section.

We compared ViSNet with the state-of-the-art algorithms, including DimeNet 16 , PaiNN 18 , SpookyNet 21 , ET 19 , GemNet 20 , UNiTE 35 , NequIP 12 , SO3KRATES 36 , Allegro 22 , MACE 23 and so on. As shown in Table  1 (MD17), Table  2 (rMD17), and Table  3 (MD22), it is remarkable that ViSNet outperformed the compared algorithms for both small (MD17 and rMD17) and large molecules (MD22) with the lowest mean absolute errors (MAE) of predicted energy and forces. On the one hand, compared with PaiNN, ET, and GemNet, ViSNet incorporated more geometric information and made full use of geometric information in ViS-MP, which contributes to the performance gains. On the other hand, compared with NequIP, Allegro, SO3KRATES, MACE, etc., ViSNet testified the effect of introducing spherical harmonics in the RGC module.

As shown in Table  4 , ViSNet also achieved superior performance for chemical property predictions on QM9. It outperformed the compared algorithms for 9 of 12 chemical properties and achieved comparable results on the remaining properties. Elaborated evaluations on Molecule3D confirmed the high prediction accuracy of ViSNet as shown in Table  5 . ViSNet achieved 33.6% and 6.51% improvements than the second-best for random split and scaffold split, respectively. Furthermore, ViSNet exhibited good portability to other multimodality methods, e.g., Transformer-M 37 and outperformed other approaches on OGB-LSC PCQM4Mv2 (see Supplementary Fig.  S1) . ViSNet also achieved the winners of PCQM4Mv2 track in the OGB-LCS@NeurIPS2022 competition when testing on unseen molecules 38 ( https://ogb.stanford.edu/neurips2022/results/ ).

To evaluate the computational efficiency of our ViSNet, following 23 , we compare the time latency of ViSNet with prevailing models in Supplementary Fig.  S2 . The latency is defined as the time it takes to compute forces on a structure (i.e., the gradient calculation for a set of input coordinates through the whole deep neural network). As shown in Supplementary Fig.  S2 , ViSNet ( L  = 2) saved 42.8% time latency compared with MACE ( L  = 2). Notably, despite the use of CG-product, Allegro had a significant speed improvement compared to NequIP and BOTNet. However, ViSNet still saved 6.1%, 4.1%, and 61% time latency compared to Allegro with L  = 1, 2, and 3, respectively.

Efficient molecular dynamics simulations

To evaluate ViSNet as the potential for MD simulations, we incorporated ViSNet that trained only with 950 samples on MD17 into the ASE simulation framework 39 to perform MD simulations for all seven kinds of organic molecules. All simulations are run with a time step τ  = 0.5 fs under the Berendsen thermostat with the other settings the same as those of the MD17 dataset. As shown in Fig.  3 , we analyzed the interatomic distance distributions derived from both AIMD simulations with ViSNet as the potential and ab initio molecular dynamics simulations at the DFT level for all seven molecules, respectively. As shown in Fig.  3 a, the interatomic distance distribution h ( r ) is defined as the ensemble average of atomic density at a radius r 9 . Figure  3 b–h illustrates the distributions derived from ViSNet are very close to those generated by DFT. We also compared the potential energy surfaces sampled by ViSNet and DFT for these molecules, respectively (Supplementary Fig.  S3 ). The consistent potential energy surfaces suggest that ViSNet can recover the conformational space from the simulation trajectories. Moreover, compared to DFT, numerous groundbreaking machine learning force fields (MLFFs), including sGDML 10 , ANI 40 , DPMD 41 , and PhysNet 42 have proven their exceptional speeds in MD simulations. Similar to such algorithms, ViSNet also exhibited significant computational cost reduction compared to DFT as shown in Supplementary Fig.  S4 and Table  S2 .

a An illustration about the atomic density at a radius r with the arbitrary atom as the center. The interatomic distance distribution is defined as the ensemble average of atomic density. b – h The interatomic distance distributions comparison between simulations by ViSNet and DFT for all seven organic molecules in MD17. The curve of ViSNet is shown using a solid blue line, while the dashed orange line is used for the DFT curve. The structures of the corresponding molecules are shown in the upper right corner. Source data are provided as a Source Data file.

To further examine the molecular properties derived from simulations driven by ViSNet, we performed 500 ps MD simulations at a constant energy ensemble (NVE) for ethanol in the MD17 dataset with a time step of τ  = 0.5 fs and 200 ps Ac-Ala3-NHMe in the MD22 dataset with a time step of τ  = 1 fs. The simulations were driven by ViSNet, sGDML, and DFT, respectively. For ethanol, we analyzed its vibrational spectra and the probability distribution of dihedral angles. For Ac-Ala3-NHMe, we investigated its vibrational spectra and potential energy surface (PES) via the Ramachandran plot. To analyze the Ramachandran plot of different simulations, the free energy value was estimated using the potential of mean force (PMF). ϕ and ψ were set as two reaction coordinates ( x , y ). All three ϕ and ψ dihedrals in Ac-Ala3-NHMe were calculated and plotted. The relative free energy value was calculated and referred to with the minimum value. To generate the landscape, 40 bins were used in both the x and y directions. Supplementary Fig.  S5 a and b demonstrate that both ViSNet and sGDML generate similar vibrational spectra, with slight differences in peak intensities compared to DFT. The probability distribution of hydroxyl angles in ethanol (Supplementary Fig.  S5 c) reveals three minima: gauche ± ( M g ± ) and trans ( M t ). Furthermore, even though ViSNet showed better performance than sGDML for various conformations in the MD22 dataset, starting from the same structure of the alanine tetrapeptide, the performance difference may not have a notable impact on the sampling efficiency for such small molecules, and thus may also lead to similar dynamics on the Ramachandran plots as shown in the Supplementary Fig.  S5 d–f. These results demonstrate that with only a few training samples, ViSNet can act with the potential to perform high-fidelity molecular dynamics simulations with much less computational cost and higher accuracy.

Applications for real-world full-atom proteins

To examine the usefulness of ViSNet in real-world applications, we made evaluations on the 166-atom mini-protein Chignolin (Fig.  4 a). Based on a Chignolin dataset consisting of about 10,000 conformations that sampled by replica exchange MD 43 and calculated at DFT level by Gaussian 16 44 in our another study 45 , 46 , we split it as training, validation, and test sets by the ratio of 8:1:1. We trained ViSNet as well as other prevailing MLFFs including ET 19 , PaiNN 18 , GemNet-OC 47 , MACE 23 , NequIP 12 and Allegro 22 and compared them with molecular mechanics (MM) 48 . The DFT results were used as the ground truth. Figure  4 b shows the free energy landscape of Chignolin and is depicted by d D3−G7 (the distance between carbonyl oxygen on the D3 backbone and nitrogen on the G7 backbone) and d E5−T8 (the distance between carbonyl oxygen on the E5 backbone and nitrogen on T8 backbone). The concentrated energy basin on the left shows the folded state and the scattered energy basin on the right shows the unfolded state. We randomly selected six structures from different regions of the potential energy surface for visualization. Among them, four structures were predicted by the model with smaller errors than the MAE while the other two with larger errors. Interestingly, all models consistently performed poorly on the structures with high potential energies (low probability of sampling) and performed well on the other structures. This implies that the sampling of conformations with high potential energies could be enhanced to ensure the generalization ability of the models.

a The visualization of Chignolin structure. The backbone is colored grey while the side chains of each residue in Chignolin are highlighted with a ball and stick. b The energy landscape of Chignolin sampled by REMD. The x -axis of the landscape is the distance between carbonyl oxygen on the D3 backbone and nitrogen on the G7 backbone, while the y -axis is the distance between carbonyl oxygen on the E5 backbone and nitrogen on the T8 backbone. Six structures were then selected for visualization. Each structure is shown as a cartoon and residues are depicted in sticks. The histograms show the absolute error between the energy difference predicted by MLFFs including ViSNet, ET, PaiNN, GemNet-OC, NequIP, Allegro, and MACE or calculated by MM, and the ground truth calculated by DFT on the corresponding structure. c The average root mean square deviation (RMSD) of the Chignolin trajectories simulated by ViSNet was calculated from 10 different trajectories. The shaded areas indicate the standard deviation range. d The MAE of each component of atomic forces during the simulations driven by ViSNet. The ground truth energies and forces were calculated using Gaussian 16. The shaded areas indicate the standard deviation range. Source data are provided as a Source Data file.

Supplementary Fig.  S6 shows the correlations between the energies predicted by MLFFs or MM and the ground truth values calculated by DFT for all conformations in the test set. ViSNet achieved a lower MAE and a higher R 2 score. From the violin plot of the absolute errors shown in Supplementary Fig.  S7 , ViSNet, PaiNN and ET exhibited smaller errors than other MLFFs while MM got a much wider range of prediction errors. Similar results can be seen in the force correlations in each component shown in Supplementary Fig.  S8 . Detailed settings about DFT and MM calculations are shown in Supplementary Materials. Furthermore, we also made a comprehensive comparison by taking model performance, training time consumption, and model size into consideration. ViSNet and other state-of-the-art algorithms such as PaiNN, ET, GemNet-OC, MACE, NequIP, and Allegro were analyzed on the Chignolin dataset and shown in Fig.  5 . Although ViSNet is marginally slower than ET and PaiNN, it introduces more geometric information, significantly enhancing its performance. When compared to GemNet, which also incorporates dihedral angles, ViSNet’s computational cost is significantly more affordable. Similarly, ViSNet proves to be computationally efficient when compared to models employing the CG-product method, such as MACE, Allegro, and NequIP.

PaiNN and ET are faster and smaller as ViSNet further incorporates dihedral calculation. ViSNet outperforms GemNet-OC due to its Runtime Geometry Calculation, reducing the explicit extraction of dihedral complexity from \({{{{{{{\mathcal{O}}}}}}}}({{{{{{{{\mathcal{N}}}}}}}}}^{3})\) to \({{{{{{{\mathcal{O}}}}}}}}({{{{{{{\mathcal{N}}}}}}}})\) . Additionally, ViSNet is also faster and smaller than MACE, Allegro, and NequIP for streamlining the CG-product. ViSNet achieves the best performance for its elaborate design, i.e., runtime geometric calculation and vector–scalar interactive message passing. Source data are provided as a Source Data file.

In addition, we performed MD simulations for Chignolin driven by ViSNet. 10 conformations were randomly selected as initial structures, and 100 ps simulations were run for each. As shown in Fig.  4 c, the RMSD for 10 simulation trajectories is shown against the simulation time. In Fig.  4 d, we displayed the MAE values of each component of the atomic forces between ViSNet and those calculated by Gaussian 16 44 at the DFT level. The simulation trajectory driven by ViSNet exhibited a small force difference for each component to quantum mechanics, which implies that ViSNet has no bias towards any force component, and thus consolidates the accuracy and potential usefulness for real-world applications.

Interpretability of ViSNet on molecular structures

Prior works have shown the effectiveness of incorporating geometric features, such as angles 16 , 20 . The primary method of geometry extraction utilized by ViSNet is the distinct inner product in its runtime geometry calculation. To this end, we illustrate a reasonable model interpretability of ViSNet by mapping the angle representations derived from the inner product of direction units in the model to the atoms in the molecular structure. We aim to bridge the gap between geometric representation in ViSNet and molecular structures. We visualized the embeddings after the inner product of direction units \(\langle {\overrightarrow{v}}_{i},{\overrightarrow{v}}_{i}\rangle\) extracted from 50 aspirin samples on the validation set. The high-dimensional embeddings were reduced to 2-dimensional space using T-SNE 49 and then clustered using DBSCAN 50 without the prior of number of clusters.

Supplementary Fig.  S9 exhibits the clustering results of nodes’ embeddings after the inner product of their corresponding direction units. We further map the clustered nodes to the atoms of aspirin chemical structure. Interestingly, the embeddings for these nodes could be distinctly gathered into several clusters shown in different colors. For example, although carbon atom C 11 and carbon atom C 12 possess different positions and connect with different atoms, their inner product \(\langle {\overrightarrow{v}}_{i},{\overrightarrow{v}}_{i}\rangle\) are clustered into the same class for holding similar substructures ({ C 11 − O 2 O 3 C 6 } and { C 12 − O 1 O 4 C 13 }). To summarize, ViSNet can discriminate different molecular substructures in the embedding space.

Ablation study

To further explore where the performance gains of ViSNet come from, we conducted a comprehensive ablation study. Specifically, we excluded the runtime angle calculation (w/o A), runtime dihedral calculation (w/o D), and both of them (w/o A&D) in ViSNet, in order to evaluate the usefulness of each part. ViSNet-improper denotes the additional improper angles and ViSNet l =1 uses the first-order spherical harmonics.

We designed some model variants with different message-passing mechanisms based on ViS-MP for scalar and vector interaction. ViSNet-N directly aggregates the dihedral information to intersecting nodes, and ViSNet-T leverages another form of dihedral calculation. The details of these model variants are elaborated in Supplementary. The results of the ablation study are shown in Supplementary Table  S3 and Supplementary Fig.  S10 . Based on the results, we can see that both kinds of directional geometric information are useful and the dihedral information contributes a little bit more to the final performance. The significant performance drop from ViSNet-N and ViSNet-T further validates the effectiveness of the ViS-MP mechanism. ViSNet-improper achieves similar performance to ViSNet for small molecules, but the contribution of improper angles is more obvious for large molecules (see Table  3 ). Furthermore, ViSNet using higher-order spherical harmonics achieves better performance.

We propose ViSNet, a geometric deep learning potential for molecular dynamics simulation. The group representation theory-based methods and the directional information-based methods are two mainstream classes of geometric deep learning potentials to enforce SE(3) equivariance 20 . ViSNet takes advantage of both sides in designing the RGC strategy and ViS-MP mechanism. On the one hand, the RGC strategy explicitly extracts and exploits the directional geometric information with computationally lightweight operations, making the model training and inference fast. On the other hand, ViS-MP employs a series of effective and efficient vector-scalar interactive operations, leading to the full use of geometric information. Furthermore, according to the many-body expansion theory 51 , 52 , 53 , the potential energy of the whole system equals the potential of each single atom plus the energy corrections from two-bodies to many-bodies. Most of the previous studies model the truncated energy correction terms hierarchically with k -hop information via stacking k message passing blocks. Different from these approaches, ViSNet encodes the angle, dihedral torsion, and improper information in a single block, which empowers the model to have a much more powerful representation ability. In addition, ViSNet’s universality or completeness is not validated by the geometric Weisfeiler–Leman (GWL) test 54 due to the inner product operation, which is computationally efficient but fails to distinguish certain atom reflection structures with the same angular information. To pass counterexamples or the GWL test, incorporating the CG-product with higher-order spherical harmonics is necessary in future studies.

Besides predicting energy, force, and chemical properties with high accuracy, performing molecular dynamics simulations with ab initio accuracy at the cost of the empirical force field is a grand challenge. ViSNet proves its usefulness in real-world ab initio molecular dynamics simulations with less computational costs and the ability of scaling to large molecules such as proteins. Extending ViSNet to support larger and more complex molecular systems will be our future research direction.

Equivariance

In the context of machine learning for atomic systems, equivariance is a pervasive concept. Specifically, the atomic vectors such as dipoles or forces must rotate in a manner consistent with the conformation coordinates. In molecular dynamics, such equivariance can be ensured by computing gradients based on a predicted conservative scalar energy. Formally, a function \({{{{{{{\mathcal{F}}}}}}}}:{{{{{{{\mathcal{X}}}}}}}}\to {{{{{{{\mathcal{Y}}}}}}}}\) is equivariant should guarantee:

where \({\rho }_{{{{{{{{\mathcal{X}}}}}}}}}(g)\) and \({\rho }_{{{{{{{{\mathcal{X}}}}}}}}}(g)\) are group representations in input and output spaces. The integration of equivariance into model parameterization has been shown to be effective, as seen in the implementation of shift-equivariance in CNNs, which is critical for enhancing the generalization capacity.

Proofs of the rotational invariance of RGC

Assume that the molecule rotates in 3D space, i.e.,

where, R   ∈   S O (3) is an arbitrary rotation matrix that satisfies:

The angular information after rotation is calculated as follows:

As shown in Eq. ( 18 ), the angle information does not change after rotation. The dihedral angular and improper information is also rotationally invariant since:

As Eq. ( 18 ) proved, the inner product has rotational invariance. Then, Eq. ( 19 ) can be further simplified as

The dihedral or improper angular information after rotation is calculated as:

As a result, Eqs. ( 18 ) and ( 21 ) have proved the rotational invariance of our proposed runtime geometry calculation (RGC).

We also provide proof of the equivariance of our ViS-MP in Supplementary Methods.

Detailed operations and modules in ViSNet

ViSNet predicts the molecular properties (e.g., energy \(\hat{E}\) , forces \(\overrightarrow{F}\in {{\mathbb{R}}}^{N\times 3}\) , dipole moment μ ) from the current states of atoms, including the atomic positions \(X\in {{\mathbb{R}}}^{N\times 3}\) and atomic numbers \(Z\in {{\mathbb{N}}}^{N}\) . The architecture of the proposed ViSNet is shown in Fig.  1 . The overall design of ViSNet follows the vector–scalar interactive message passing as illustrated from Eqs. ( 8 )–( 11 ). First, an embedding block encodes the atom numbers and edge distances into the embedding space. Then, a series of ViSNet blocks update the node-wise scalar and vector representations based on their interactions. A residual connection is placed between two ViSNet blocks. Finally, stacked corresponding gated equivariant blocks proposed by 18 are attached to the output block for specific molecular property prediction.

The embedding block

ViSNet expands the direct node and edge embedding with their neighbors. It first embeds atomic chemical symbol z i , and calculates the edge representation whose distances within the cutoff through radial basis functions (RBF). Then the initial embedding of the atom i , its 1-hop neighbors j and the directly connected edge e i j within cutoff are fused together as the initial node embedding \({h}_{i}^{0}\) and edge embedding \({f}_{ij}^{0}\) . In summary, the embedding block is given by:

\({{{{{{{\mathcal{N}}}}}}}}(i)\) denotes the set of 1-hop neighboring nodes of node i , and j is one of its neighbors. The embedding process is elaborated in Supplementary. The initial vector embedding \({\overrightarrow{v}}_{i}\) is set to \(\overrightarrow{0}\) . The vector embeddings \(\overrightarrow{v}\) are projected into the embedding space by following 18 ; \(\overrightarrow{v}\in {{\mathbb{R}}}^{N\times 3\times F}\) and F is the size of hidden dimension. The advantage of such projection is to assign a unique high-dimensional representation for each embedding to discriminate from each other. Further discussions on its effectiveness and interpretability are given in the Results section.

The Scalar2Vec module

In the Scalar2Vec module, the vector embedding \(\overrightarrow{v}\) is updated by both the scalar messages derived from node and edge scalar embeddings (Eq. ( 8 )) and the vector messages with inherent geometric information (Eq. ( 9 )). The message of each atom is calculated through an Edge-Fusion Graph Attention module, which fuses the node and edge embeddings and computes the attention scores. The fusion of the node and edge embeddings could be the concatenation operation, Hadamard product, or adding a learnable bias 55 . We leverage the Hadamard product and the vanilla multi-head attention mechanism borrowed from Transformer 56 for edge-node fusion.

Following 19 , we pass the fused representations through a nonlinear activation function as shown in Eq. ( 23 ). The value ( V ) in the attention mechanism is also fused by edge features before being multiplied by attention scores weighted by a cosine cutoff as shown in Eq. ( 24 ),

where l   ∈  {0, 1, 2,  ⋯   ,  L } is the index of the block, σ denotes the activation function (SiLU in this paper), W is the learnable weight matrix,  ⊙  represents the Hadamard product, ϕ (  ⋅  ) denotes the cosine cutoff and Dense(  ⋅  ) refers to one learnable weight matrix with an activation function. For brevity, we omit the learnable bias for linear transformation on scalar embedding in equations, and there is no bias for vector embedding to ensure the equivariance.

Then, the computed \({m}_{ij}^{l}\) is used to produce the geometric messages \({\overrightarrow{m}}_{ij}^{l}\) for vectors:

And the vector embedding \({\overrightarrow{v}}^{l}\) is updated by:

The Vec2Scalar module

In the Vec2Scalar module, the node embedding \({h}_{i}^{l}\) and edge embedding \({f}_{ij}^{l}\) are updated by the geometric information extracted by the RGC strategy, i.e., angles (Eq. ( 10 )) and dihedrals (Eq. ( 11 )), respectively. The residual node embedding \({{\Delta }}{h}_{i}^{l+1}\) , is calculated by a Hadamard product between the runtime angle information and the aggregated scalar messages with a gated residual connection:

To compute the residual edge embedding \({{\Delta }}{f}_{ij}^{l+1}\) , we perform the Hadamard product of the runtime dihedral information with the transformed edge embedding:

After the residual hidden representations are calculated, we add them to the original input of block l and feed them to the next block.

A comprehensive version that includes improper angles is depicted in Supplementary Methods.

The output block

Following PaiNN 18 , we update the scalar embedding and vector embedding of nodes with multiple gated equivariant blocks:

where [  ⋅  ,  ⋅  ] is the tensor concatenation operation. The final scalar embedding \({h}_{i}^{L}\in {{\mathbb{R}}}^{N\times 1}\) and vector embedding \({\overrightarrow{v}}_{i}^{L}\in {{\mathbb{R}}}^{N\times 3\times 1}\) are used to predict various molecular properties.

On QM9, the molecular dipole is calculated as follows:

where \({\overrightarrow{r}}_{c}\) denotes the center of mass. Similarly, for the prediction of electronic spatial extent 〈 R 2 〉, we use the following equation:

For the remaining 10 properties y , we simply aggregate the final scalar embedding of nodes as follows:

For models trained on the molecular dynamics datasets including MD17, revised MD17, and Chignolin, the total potential energy is obtained as the sum of the final scalar embedding of the nodes. As an energy-conserving potential, the forces are then calculated using the negative gradients of the predicted total potential energy with respect to the atomic coordinates:

Statistics and reproducibility

For the QM9 dataset, we randomly split it into 110,000 samples as the train set, 10,000 samples as the validation set, and the rest as the test set by following the previous studies 18 , 19 . For the Molecule3D and OGB-LSC PCQM4Mv2 datasets, the splitting has been provided in their paper 32 , 33 .

To evaluate the effectiveness of ViSNet in simulation data, ViSNet was trained on MD17 and rMD17 with a limited data setting, which consists of only 950 uniformly sampled conformations for model training and 50 conformations for validation for each molecule. For the MD22 dataset, we use the same number of molecules as in ref. 30 for training and validation, and the rest as the test set.

Furthermore, the whole Chignolin dataset was randomly split into 80%, 10%, and 10% as the training, validation, and test datasets. Six representative conformations were picked from the test set for illustration.

Experimental settings

For the QM9 dataset, we adopted a batch size of 32 and a learning rate of 1e−4 for all the properties. For the Molecule3D dataset, we adopted a larger batch size of 512 and a learning rate of 2e−4. For the OGB-LSC PCQM4Mv2 dataset, we trained our model in a mixed 2D/3D mode with a batch size of 256 and a learning rate of 2e−4. The mean squared error (MSE) loss was used for model training. For the molecular dynamic dataset including MD17, rMD17, MD22, and Chignolin, we leveraged a combined MSE loss for energy and force prediction. The weight of energy loss was set to 0.05. The weight of force loss was set to 0.95. The batch size was chosen from 2, 4, 8 due to the GPU memory and the learning rate was chosen from 1e−4 to 4e−4 for different molecules. The cutoff was set to 5 for small molecules in QM9, MD17, rMD17, and Molecule3D, and changed to 4 for Chignolin in order to reduce the number of edges in the molecular graphs. For the MD22 dataset, the cutoff of relatively small molecules was set to 5, that of bigger molecules was set to 4. Cutoff was not used in the OGB-LSC PCQM4Mv2 dataset. We used the learning rate decay if the validation loss stopped decreasing. The patience was set to 5 epochs for Molecule3D, 15 epochs for QM9, and 30 epochs for MD17, rMD17, MD22, and Chignolin. The learning rate decay factor was set to 0.8 for these models. Training is stopped if a maximum number of epochs is reached, or the validation loss does not improve for a maximum number of early stopping patience. The ViSNet model trained on the molecular dynamic datasets and Molecule3D had 9 hidden layers and the embedding dimension was set to 256. We used a larger model for the QM9 dataset, i.e., the embedding dimension changed to 512. For the OGB-LSC PCQM4Mv2 dataset, we use the 12-layer and 768-dimension Transformer-M 37 as the backbone. More details about the hyperparameters of ViSNet can be found in Supplementary Table  S4 . Experiments were conducted on NVIDIA 32G-V100 GPUs.

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

Data availability

All relevant data supporting the key findings of this study are available within the article and its Supplementary Information files. MD17 dataset [ http://www.quantum-machine.org/gdml/data/npz ], MD22 dataset [ http://www.quantum-machine.org/gdml/data/npz ], rMD17 dataset [ https://archive.materialscloud.org/record/file?filename=rmd17.tar.bz2&record_id=466 ], QM9 dataset [ https://deepchemdata.s3-us-west-1.amazonaws.com/datasets/molnet_publish/qm9.zip ], Molecule3D dataset [ https://github.com/divelab/MoleculeX/tree/molx/Molecule3D ], OGB-LSC PCQM4Mv2 dataset [ https://ogb.stanford.edu/docs/lsc/pcqm4mv2 ] and Chignolin dataset [ https://github.com/microsoft/AI2BMD/tree/ViSNet/chignolin_data ].  Source data are provided with this paper.

Code availability

Most experiments were run with Python with version 3.9.15, Pytorch with version 1.11.0, Pytorch Geometric with version 2.1.0, and Pytorch Lightning with version 1.8.0. The code used to reproduce our results is available at https://github.com/microsoft/AI2BMD/tree/ViSNet 57 . Matplotlib and Seaborn were used for plotting figures.

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Acknowledgements

We would like to express our sincere gratitude to S. Chmiela, H.E. Sauceda, K.R. Müller, and A. Tkatchenko, for their invaluable assistance in performing the simulations and analyzing the vibrational spectra. Their extensive expertise and knowledge greatly contributed to the completion of the supplementary experiments, making our manuscript more solid.

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These authors contributed equally: Yusong Wang, Tong Wang, Shaoning Li.

Authors and Affiliations

Microsoft Research AI4Science, 100080, Beijing, China

Yusong Wang, Tong Wang, Shaoning Li, Xinheng He, Mingyu Li, Zun Wang, Bin Shao & Tie-Yan Liu

National Key Laboratory of Human–Machine Hybrid Augmented Intelligence, National Engineering Research Center for Visual Information and Applications, and Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, 710049, Xi’an, China

Yusong Wang & Nanning Zheng

The CAS Key Laboratory of Receptor Research and State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China

University of Chinese Academy of Sciences, 100049, Beijing, China

Medicinal Chemistry and Bioinformatics Center, School of Medicine, Shanghai Jiaotong University, Shanghai, 200025, China

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T.W. led, conceived, and designed the study. T.W. is the lead contact. Y.W., S.L., X.H., and M.L. conducted the work when they were visiting Microsoft Research. S.L., Y.W., and T.W. carried out algorithm design. Y.W., S.L., X.H., and T.W. carried out experiments, evaluations, analysis, and visualization. Y.W. and S.L. wrote the original manuscript. T.W., X.H., M.L., Z.W., and B.S. revised the manuscript. N.Z. and T.-Y.L. contributed to the writing. All authors reviewed the final manuscript.

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Correspondence to Tong Wang or Bin Shao .

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T.W., B.S., and T.-Y.L. have been filing a patent on ViSNet model. The remaining authors declare no competing interests.

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Wang, Y., Wang, T., Li, S. et al. Enhancing geometric representations for molecules with equivariant vector-scalar interactive message passing. Nat Commun 15 , 313 (2024). https://doi.org/10.1038/s41467-023-43720-2

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Evaluation of Class-10 English Textbooks: Case Study Based on NCF 2023

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Textbook evaluation, an interesting area in the field of applied linguistics, has a wide scope for research. The purpose of this research paper is to state the aims and objectives stated in NCF 2023(National Curriculum Framework) concerning the English language course textbook, to list out the current challenges faced in schools as stated in NCF 2023, to explain how a textbook can be evaluated, and to evaluate textbooks based on the principles of NCF 2023. Both qualitative and quantitative studies have been conducted to assess whether the learning outcomes and goals are achieved or not. For this purpose, I have chosen Class-10 English textbooks across two different boards, one from the CBSE board (The B.V.B school) and the other from the Tamil Nadu State Board (Bharathi Vidhya Bhavan Matriculation Higher Secondary school). Evaluation has been done by collecting information from teachers and students of both the schools in the during-use and post-use stages to get feedback on how well the books work in practice, and how effectively the aims are achieved.

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