World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
19483
World Ranking
6297
National Ranking
2816

Michael Hucka 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 Michael Hucka 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: 147 publications — 26th percentile

26% of scientists in this discipline score the same or lower.

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

Michael Hucka 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 Michael Hucka 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: 47 D-Index — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Overview

Michael Hucka is affiliated with the California Institute of Technology in the United States. Their research primarily spans the fields of Biochemistry, Genetics and Molecular Biology, and Decision Sciences, with notable subfields including Molecular Biology, Information Systems and Management, Information Systems, and Management Science and Operations Research.

Their work addresses a range of topics including Gene Regulatory Network Analysis, Bioinformatics and Genomic Networks, Microbial Metabolic Engineering and Bioproduction, Scientific Computing and Data Management, Research Data Management Practices, Data Quality and Management, and Biomedical Text Mining and Ontologies.

Among the recent papers authored or co-authored by Michael Hucka are:

  • <scp>SBML</scp> Level 3: an extensible format for the exchange and reuse of biological models (2020), Molecular Systems Biology
  • The first 10 years of the international coordination network for standards in systems and synthetic biology (COMBINE) (2020), Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics
  • Specifications of standards in systems and synthetic biology: status and developments in 2020 (2020), Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics
  • Nine best practices for research software registries and repositories (2022), PeerJ Computer Science
  • Systems biology markup language (SBML) level 3 package: multistate, multicomponent and multicompartment species, version 1, release 2 (2020), Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics

Frequent co-authors collaborating with Michael Hucka include:

  • Sarah Keating
  • Matthias König
  • Chris J. Myers
  • Dagmar Waltemath
  • Lucian P. Smith

Michael Hucka's publications are commonly found in the following venues:

  • Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics
  • arXiv (Cornell University)
  • Molecular Systems Biology
  • PeerJ Computer Science
  • VU Research Portal

Best Publications

  • The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models.

    M. Hucka;A. Finney;H. M. Sauro;H. Bolouri;H. Bolouri

  • Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0

    Laurent Heirendt;Sylvain Arreckx;Thomas Pfau;Sebastián N. Mendoza

  • A community-driven global reconstruction of human metabolism

    Ines Thiele;Neil Swainston;Ronan M T Fleming;Andreas Hoppe

  • The Systems Biology Graphical Notation

    Nicolas Le Novere;Michael Hucka;Huaiyu Mi;Stuart Moodie

  • BioModels Database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems

    Nicolas Le Novère;Benjamin J. Bornstein;Alexander Broicher;Mélanie Courtot

  • The BioPAX community standard for pathway data sharing

    Emek Demir;Emek Demir;Michael P. Cary;Suzanne Paley;Ken Fukuda

  • Minimum information requested in the annotation of biochemical models (MIRIAM)

    Nicolas Le Novère;Andrew Finney;Michael Hucka;Upinder S. Bhalla

  • A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology

    Markus Herrgard;Neil Swainston;Paul Dobson;Warwick B. Dunn

  • Biomodels database: an enhanced curated and annotated resource for published quantitative kinetic models

    Chen Li;Marco Donizelli;Nicolas Rodriguez;Harish Dharuri

  • LibSBML: an API library for SBML.

    Benjamin J. Bornstein;Sarah M. Keating;Akiya Jouraku;Michael Hucka

  • Rules for Modeling Signal-Transduction Systems

    William S. Hlavacek;James R. Faeder;Michael L. Blinov;Richard G. Posner

  • BioModels—15 years of sharing computational models in life science

    Rahuman S Malik-Sheriff;Mihai Glont;Tung V N Nguyen;Krishna Tiwari;Krishna Tiwari

  • Next Generation Simulation Tools: The Systems Biology Workbench and BioSPICE Integration

    Herbert M. Sauro;Michael Hucka;Andrew Finney;Cameron Wellock

  • Controlled vocabularies and semantics in systems biology

    Mélanie Courtot;Nick Juty;Christian Knüpfer;Dagmar Waltemath

  • BioModels: ten-year anniversary

    Vijayalakshmi Chelliah;Nick S. Juty;Ishan Ajmera;Raza Ali

  • Evolving a lingua franca and associated software infrastructure for computational systems biology: the Systems Biology Markup Language (SBML) project

    M. Hucka;A. Finney;B.J. Bornstein;S.M. Keating

  • Reproducible computational biology experiments with SED-ML--the Simulation Experiment Description Markup Language.

    Dagmar Waltemath;Richard R. Adams;Frank T. Bergmann;Michael Hucka

  • SBML Level 3: an extensible format for the exchange and reuse of biological models

    Sarah M. Keating;Sarah M. Keating;Dagmar Waltemath;Matthias König;Fengkai Zhang

  • Systems biology markup language: Level 2 and beyond

    A. Finney;M. Hucka

  • The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core.

    Michael Hucka;Frank T. Bergmann;Claudine Chaouiya;Andreas Dräger

  • Towards NeuroML: Model Description Methods for Collaborative Modelling in Neuroscience

    Nigel H. Goddard;Michael Hucka;Fred Howell;Hugo Cornelis

Frequent Co-Authors

Nicolas Le Novère
Nicolas Le Novère Babraham Institute
Falk Schreiber
Falk Schreiber University of Konstanz
Herbert M. Sauro
Herbert M. Sauro University of Washington
Chris J. Myers
Chris J. Myers University of Colorado Boulder
Jacky L. Snoep
Jacky L. Snoep Stellenbosch University
Pedro Mendes
Pedro Mendes University of Connecticut
Hiroaki Kitano
Hiroaki Kitano Okinawa Institute of Science and Technology
John C. Doyle
John C. Doyle California Institute of Technology
Gary D. Bader
Gary D. Bader University of Toronto
Bernhard O. Palsson
Bernhard O. Palsson University of California, San Diego

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