World's Best Scientists 2026 revealed!
Protein Science
H-index 49

Protein Science

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Molecular Biology 70 28 48 16
Biology and Biochemistry 100 294 381 40

Additional Metrics

Number of Best Scientists*: 612
Documents by Best Scientists*: 686
Top 100 Ranked Scientists*: 20
SCIMAGO H-index: 204
SCIMAGO SJR: 4.657
Impact Factor: 5.2

Overview

Top Research Topics at Protein Science?

Protein Science aims to foster the development of research in Biochemistry, Protein structure, Crystallography, Stereochemistry and Protein folding. Most of the works presented in Protein Science deals with Biochemistry but it intersects with the subject of Biophysics. Topics in Protein structure were tackled in line with various other fields like Plasma protein binding and Computational biology.

Issues in Crystallography were discussed, taking into consideration concepts from other disciplines like Hydrogen bond, Nuclear magnetic resonance spectroscopy and Protein secondary structure. Stereochemistry research featured in the journal incorporates concerns from various other topics such as Mutant and Active site. The journal addresses concerns in Protein folding which are intertwined with other disciplines, such as Folding (chemistry) and Native state.

Peptide sequence research discussed connects with the study of Peptide.

  • Biochemistry (27.79%)
  • Protein structure (23.70%)
  • Crystallography (19.83%)

What are the most cited papers published in the journal?

  • How to measure and predict the molar absorption coefficient of a protein. (3272 citations)
  • Verification of protein structures: Patterns of nonbonded atomic interactions (2063 citations)
  • Thioflavine T interaction with synthetic Alzheimer's disease beta-amyloid peptides: detection of amyloid aggregation in solution. (1897 citations)

Research areas of the most cited articles at Protein Science:

The most cited publications focus largely on the fields of Protein structure, Biochemistry, Crystallography, Protein folding and Peptide sequence. The most cited publications focus on Protein structure but the discussions also offer insight into other areas such as Plasma protein binding, Protein secondary structure, Stereochemistry, Computational biology and Binding site. Many of the studies tackled in the journal publications connect Biochemistry with a similar field of study like Biophysics.

What topics the last edition of the journal is best known for?

  • Enzyme
  • Gene
  • Quantum mechanics

The previous edition focused in particular on these issues:

The journal focuses largely on the fields of Biophysics, Computational biology, Biochemistry, Cell biology and Mathematical physics. Some problems in Biophysics that were presented in Protein Science overlapped with concepts under Protein aggregation, RNA, Mutant, Folding (chemistry) and Phosphorylation. While Computational biology is the focus of it, it also provided insights into the studies of Protein structure and Protein Data Bank (RCSB PDB).

Enzyme is a key component of Biochemistry research discussed in it. Protein Science links adjacent topics like Enzyme with Stereochemistry.

The most cited articles from the last journal are:

  • UCSF ChimeraX: Structure visualization for researchers, educators, and developers. (355 citations)
  • The BioGRID database: A comprehensive biomedical resource of curated protein, genetic, and chemical interactions. (87 citations)
  • DynaMut2: Assessing changes in stability and flexibility upon single and multiple point missense mutations. (25 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

The top authors publishing in Protein Science (based on the number of publications) are:

  • David Eisenberg (50 papers) absent at the last edition,
  • Brian W. Matthews (49 papers) published 3 papers at the last edition,
  • David Baker (42 papers) absent at the last edition,
  • Shigeyuki Yokoyama (36 papers) absent at the last edition,
  • Hazel M. Holden (34 papers) published 3 papers at the last edition the same number as at the previous edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Only papers with recognized affiliations are considered

The top affiliations publishing in Protein Science (based on the number of publications) are:

  • Max Planck Society (266 papers) published 15 papers at the last edition, 7 more than at the previous edition,
  • National Institutes of Health (177 papers) published 4 papers at the last edition, 3 more than at the previous edition,
  • University of California, Los Angeles (167 papers) absent at the last edition,
  • University of Washington (150 papers) published 2 papers at the last edition, 7 less than at the previous edition,
  • University of California, San Francisco (138 papers) published 5 papers at the last edition, 2 more than at the previous edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 3.53% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 14.23% were posted by at least one author from the top 10 institutions publishing in the journal. Another 4.07% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 15.04% of all publications and 66.67% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Top Publications

  • UCSF ChimeraX: Structure visualization for researchers, educators, and developers.

    Eric F Pettersen;Thomas D Goddard;Conrad C Huang;Elaine C Meng

    (2021)
    6585 Citations
  • The BioGRID database: A comprehensive biomedical resource of curated protein, genetic, and chemical interactions.

    Rose Oughtred;Jennifer Rust;Christie Chang;Bobby-Joe Breitkreutz

    (2021)
    1809 Citations
  • <scp>UCSF ChimeraX</scp>: Tools for structure building and analysis

    (2023)
    1093 Citations
  • PANTHER: Making genome-scale phylogenetics accessible to all.

    Paul D Thomas;Dustin Ebert;Anushya Muruganujan;Tremayne Mushayahama

    (2021)
    865 Citations
  • DALI and the persistence of protein shape.

    Liisa Holm

    (2020)
    620 Citations
  • DALI shines a light on remote homologs: One hundred discoveries

    (2022)
    411 Citations
  • DynaMut2: Assessing changes in stability and flexibility upon single and multiple point missense mutations.

    Carlos H.M. Rodrigues;Carlos H.M. Rodrigues;Douglas E.V. Pires;Douglas E.V. Pires;David B. Ascher;David B. Ascher;David B. Ascher

    (2021)
    364 Citations
  • Crystal structure of Nsp15 endoribonuclease NendoU from SARS-CoV-2.

    Youngchang Kim;Youngchang Kim;Robert Jedrzejczak;Robert Jedrzejczak;Natalia I. Maltseva;Natalia I. Maltseva;Mateusz Wilamowski

    (2020)
    352 Citations
  • RCSB Protein Data Bank: Enabling biomedical research and drug discovery

    David S Goodsell;David S Goodsell;Christine Zardecki;Luigi Di Costanzo;Jose M Duarte

    (2020)
    281 Citations
  • Using evolutionary data to make sense of macromolecules with a “face‐lifted” ConSurf

    (2023)
    257 Citations

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