World's Best Scientists 2026 revealed!
John P. Overington

John P. Overington

D-Index & Metrics

Computer Science

D-Index
51
Citations
29994
World Ranking
5194
National Ranking
310

John P. Overington 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 John P. Overington 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: 127 publications — 17th percentile

17% of scientists in this discipline score the same or lower.

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

John P. Overington 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 John P. Overington 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: 51 D-Index — 63rd percentile

63% of scientists in this discipline score the same or lower.

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

Overview

John P. Overington is affiliated with Exscientia in the United Kingdom and focuses their research primarily in the field of Medicine. Their work covers several specialized subfields including Molecular Biology, Computational Theory and Mathematics, Epidemiology, Spectroscopy, and Surgery.

Their recent publications address diverse topics within healthcare and computational sciences. Notable papers include:

  • PCSK9 monoclonal antibodies for the primary and secondary prevention of cardiovascular disease, 2020, Cochrane Database of Systematic Reviews
  • Artificial intelligence, drug repurposing and peer review, 2020, Nature Biotechnology
  • AI3SD Interview with Professor John Overington, 2020, ePrints Soton (University of Southampton)
  • EXTH-46. ARTIFICIAL INTELLIGENCE-BASED IDENTIFICATION OF COMBINED VANDETANIB AND EVEROLIMUS IN THE TREATMENT OF ACVR1-MUTANT DIFFUSE INTRINSIC PONTINE GLIOMA, 2020, Neuro-Oncology
  • AI3SD Video: Drug Repositioning for COVID-19, 2020, ePrints Soton (University of Southampton)

Frequent co-authors collaborating with Overington include:

  • Amand F. Schmidt
  • John-Paul Carter
  • Lucy S Pearce
  • John T. Wilkins
  • Aroon D. Hingorani

Their research has been published mostly in the following venues:

  • ePrints Soton (University of Southampton)
  • Cochrane Database of Systematic Reviews
  • Nature Biotechnology
  • Neuro-Oncology
  • SSRN Electronic Journal

Key topics addressed in Overington's work span multiple aspects of healthcare and computational methods, such as:

  • Computational Drug Discovery Methods
  • Lipoproteins and Cardiovascular Health
  • Pharmaceutical Economics and Policy
  • Artificial Intelligence in Healthcare and Education
  • Misinformation and Its Impacts
  • Academic Publishing and Open Access
  • Glioma Diagnosis and Treatment

Best Publications

  • How many drug targets are there

    John P. Overington;Bissan Al-Lazikani;Andrew L. Hopkins

  • ChEMBL: a large-scale bioactivity database for drug discovery

    Anna Gaulton;Louisa J. Bellis;A. Patricia Bento;Jon Chambers

  • A comprehensive map of molecular drug targets

    Rita Santos;Rita Santos;Oleg Ursu;Anna Gaulton;A. Patrícia Bento

  • The ChEMBL database in 2017.

    Anna Gaulton;Anne Hersey;Michał Nowotka;A. Patrícia Bento

  • The ChEMBL bioactivity database: an update

    A. Patrícia Bento;Anna Gaulton;Anne Hersey;Louisa J. Bellis

  • An atlas of genetic influences on human blood metabolites

    So-Youn Shin;Eric B Fauman;Ann-Kristin Petersen;Jan Krumsiek

  • The druggable genome and support for target identification and validation in drug development.

    Chris Finan;Anna Gaulton;Felix A. Kruger;R. Thomas Lumbers

  • The promise and peril of chemical probes.

    Cheryl H. Arrowsmith;James E. Audia;Christopher Austin;Jonathan Baell

  • ChEMBL web services: streamlining access to drug discovery data and utilities.

    Mark Davies;Michal Nowotka;George Papadatos;Nathan Dedman

  • HOMSTRAD: A database of protein structure alignments for homologous families

    Kenji Mizuguchi;Charlotte M. Deane;Tom L. Blundell;John P. Overington

  • Can we rationally design promiscuous drugs

    Andrew L Hopkins;Jonathan S Mason;John P Overington

  • JOY: protein sequence-structure representation and analysis.

    Kenji Mizuguchi;Charlotte M. Deane;Tom L. Blundell;Mark S. Johnson

  • Unexplored therapeutic opportunities in the human genome.

    Tudor I. Oprea;Cristian G. Bologa;Søren Brunak;Allen Campbell

  • A structural basis for sequence comparisons : an evaluation of scoring methodologies

    Mark S. Johnson;John P. Overington

  • Derivation of rules for comparative protein modeling from a database of protein structure alignments

    Andrej ŠAli;John P. Overington

  • Genomic-scale prioritization of drug targets: the TDR Targets database

    Fernán Agüero;Bissan Al-Lazikani;Martin Aslett;Matthew Berriman

  • Comprehensive characterization of the Published Kinase Inhibitor Set

    Jonathan M. Elkins;Vita Fedele;Marta Szklarz;Kamal R. Abdul Azeez

  • 18th Sir Hans Krebs lecture. Knowledge-based protein modelling and design

    Tom Blundell;Devon Carney;Stephen Gardner;Fiona Hayes

  • PSICQUIC and PSISCORE: accessing and scoring molecular interactions

    Bruno Aranda;Hagen Blankenburg;Samuel Kerrien;Fiona S L Brinkman

  • Pharos: Collating protein information to shed light on the druggable genome

    Dac-Trung Nguyen;Stephen L. Mathias;Cristian Bologa;Søren Brunak

Frequent Co-Authors

Tom L. Blundell
Tom L. Blundell University of Cambridge
Andrej Sali
Andrej Sali University of California, San Francisco
Jonathan B. Baell
Jonathan B. Baell Monash University
Stuart A. Ralph
Stuart A. Ralph University of Melbourne
Guri Giaever
Guri Giaever University of British Columbia
Sergio Wittlin
Sergio Wittlin Swiss Tropical and Public Health Institute
Corey Nislow
Corey Nislow University of British Columbia
Vicky M. Avery
Vicky M. Avery Griffith University
Kiaran Kirk
Kiaran Kirk Australian National University
Elizabeth A. Winzeler
Elizabeth A. Winzeler University of California, San Diego

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