World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
11719
World Ranking
6099
National Ranking
2745

W. John Wilbur publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where W. John Wilbur sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 163 publications — 32nd percentile

32% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

W. John Wilbur D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where W. John Wilbur sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 48 D-Index — 58th percentile

58% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

W. John Wilbur is affiliated with the National Institutes of Health in the United States. Their research spans multiple fields including Computer Science, Biochemistry, Genetics and Molecular Biology, as well as Medicine. The main areas of study focus on Artificial Intelligence, Molecular Biology, Genetics, Health Informatics, and Infectious Diseases.

The scientist's work covers several specific topics, with notable concentration in:

  • Topic Modeling
  • Biomedical Text Mining and Ontologies
  • Machine Learning in Healthcare
  • Artificial Intelligence in Healthcare and Education
  • Natural Language Processing Techniques
  • Race, Genetics, and Society
  • Forensic and Genetic Research

W. John Wilbur has published research in multiple venues, frequently contributing to:

  • Bioinformatics
  • arXiv (Cornell University)
  • The American Journal of Human Genetics
  • BMC Medical Informatics and Decision Making
  • Journal of the American Medical Informatics Association

Selected recent papers by Wilbur include:

  • MedCPT: Contrastive Pre-trained Transformers with large-scale PubMed search logs for zero-shot biomedical information retrieval, 2023, Bioinformatics
  • Evolving use of ancestry, ethnicity, and race in genetics research-A survey spanning seven decades, 2021, The American Journal of Human Genetics
  • Deep learning with sentence embeddings pre-trained on biomedical corpora improves the performance of finding similar sentences in electronic medical records, 2020, BMC Medical Informatics and Decision Making
  • Better synonyms for enriching biomedical search, 2020, Journal of the American Medical Informatics Association
  • MedCPT: Contrastive Pre-trained Transformers with Large-scale PubMed Search Logs for Zero-shot Biomedical Information Retrieval, 2023, arXiv (Cornell University)

Frequent co-authors include:

  • Zhiyong Lu
  • Qingyu Chen
  • Donald C. Comeau
  • Lana Yeganova
  • Qiao Jin

Best Publications

  • Database resources of the National Center for Biotechnology Information

    Unknown

  • Overview of BioCreative II gene mention recognition

    Larry Smith;Lorraine K Tanabe;Rie Johnson nee Ando;Cheng-Ju Kuo

  • Tagging gene and protein names in biomedical text.

    Lorraine K. Tanabe;W. John Wilbur

  • The automatic identification of stop words

    W. John Wilbur;Karl Sirotkin

  • GeneWays: a system for extracting, analyzing, visualizing, and integrating molecular pathway data

    Andrey Rzhetsky;Ivan Iossifov;Tomohiro Koike;Michael Krauthammer

  • GENETAG: a tagged corpus for gene/protein named entity recognition.

    Lorraine K. Tanabe;Natalie Xie;Lynne H. Thom;Wayne Matten

  • PubMed related articles: a probabilistic topic-based model for content similarity.

    Jimmy J. Lin;Jimmy J. Lin;W. John Wilbur

  • MedPost: a part-of-speech tagger for bioMedical text

    L. Smith;T. Rindflesch;W. J. Wilbur

  • SplicePort—An interactive splice-site analysis tool

    Rezarta Islamaj Dogan;Lise Getoor;W. John Wilbur;Stephen M. Mount

  • Evaluation of query expansion using MeSH in PubMed

    Zhiyong Lu;Won Kim;W. John Wilbur

  • Evaluation of text-mining systems for biology: overview of the Second BioCreative community challenge

    Martin Krallinger;Alexander Morgan;Larry Smith;Florian Leitner

  • Genes, Themes, and Microarrays: Using Information Retrieval for Large-Scale Gene Analysis

    Hagit Shatkay;Stephen Edwards;W. John Wilbur;Mark Boguski

  • The NLM Indexing Initiative.

    Alan R. Aronson;Olivier Bodenreider;H. Florence Chang;Susanne M. Humphrey

  • New directions in biomedical text annotation: definitions, guidelines and corpus construction

    W John Wilbur;Andrey Rzhetsky;Hagit Shatkay

  • BioC: a minimalist approach to interoperability for biomedical text processing

    Donald C. Comeau;Rezarta Islamaj Doğan;Paolo Ciccarese;Kevin Bretonnel Cohen

  • Extracting drug-drug interactions from literature using a rich feature-based linear kernel approach

    Sun Kim;Haibin Liu;Lana Yeganova;W. John Wilbur

  • The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text

    Martin Krallinger;Miguel Vazquez;Florian Leitner;David Salgado

  • Modelling neutral and selective evolution of protein folding.

    David J. Lipman;W. John Wilbur

  • The gene normalization task in BioCreative III

    Zhiyong Lu;Hung-Yu Kao;Chih-Hsuan Wei;Minlie Huang

  • Multi-dimensional classification of biomedical text

    Hagit Shatkay;Fengxia Pan;Andrey Rzhetsky;W. John Wilbur

  • An analysis of statistical term strength and its use in the indexing and retrieval of molecular biology texts.

    W.John Wilbur;Yiming Yang;Yiming Yang

  • Database resources of the National Center for Biotechnology Information

    Unknown

Frequent Co-Authors

Zhiyong Lu
Zhiyong Lu National Institutes of Health
Jimmy Lin
Jimmy Lin University of Waterloo
Martin Krallinger
Martin Krallinger Barcelona Supercomputing Center
Cathy H. Wu
Cathy H. Wu University of Delaware
Karin Verspoor
Karin Verspoor RMIT University
Hong-Jie Dai
Hong-Jie Dai Southwest University
Alan R. Aronson
Alan R. Aronson National Institutes of Health
Dina Demner-Fushman
Dina Demner-Fushman National Institutes of Health
Hong Yu
Hong Yu University of Massachusetts Lowell
Andrew Chatr-aryamontri
Andrew Chatr-aryamontri University of Montreal

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