World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
11856
World Ranking
5810
National Ranking
2641

Eugene N. Muratov 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 Eugene N. Muratov 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: 144 publications — 24th percentile

24% of scientists in this discipline score the same or lower.

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

Eugene N. Muratov 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 Eugene N. Muratov 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: 49 D-Index — 60th percentile

60% of scientists in this discipline score the same or lower.

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

Overview

Eugene N. Muratov is affiliated with the University of North Carolina at Chapel Hill in the United States. Their research work predominantly falls within the field of Biochemistry, Genetics and Molecular Biology with a significant focus on Molecular Biology and Computational Theory and Mathematics. Their scientific contributions also extend into Infectious Diseases, Public Health, Environmental and Occupational Health, and Organic Chemistry.

The main topics addressed in their publications include Computational Drug Discovery Methods, Bioinformatics and Genomic Networks, SARS-CoV-2 and COVID-19 Research, Animal Testing and Alternatives, Metabolomics and Mass Spectrometry Studies, Research on Leishmaniasis Studies, and Vaccines and Immunoinformatics Approaches.

Recent papers authored or co-authored by Eugene N. Muratov include:

  • QSAR without borders, 2020, Chemical Society Reviews
  • A critical overview of computational approaches employed for COVID-19 drug discovery, 2021, Chemical Society Reviews
  • CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity, 2020, Environmental Health Perspectives
  • STopTox: An in Silico Alternative to Animal Testing for Acute Systemic and Topical Toxicity, 2022, Environmental Health Perspectives
  • Synergistic and Antagonistic Drug Combinations against SARS-CoV-2, 2020, Molecular Therapy

Eugene has collaborated frequently with several co-authors, including:

  • Alexander Tropsha
  • Vinícius M. Alves
  • Carolina Horta Andrade
  • Rodolpho C. Braga
  • Luciana Scotti

Their publications are often found in venues such as UNC Libraries, bioRxiv (Cold Spring Harbor Laboratory), OPAL (Open@LaTrobe) (La Trobe University), Journal of Chemical Information and Modeling, and Environmental Health Perspectives.

Best Publications

  • QSAR Modeling: Where have you been? Where are you going to?

    Artem Cherkasov;Eugene N. Muratov;Eugene N. Muratov;Denis Fourches;Alexandre Varnek

  • Trust, But Verify: On the Importance of Chemical Structure Curation in Cheminformatics and QSAR Modeling Research

    Denis Fourches;Eugene N. Muratov;Alexander Tropsha

  • QSAR without borders

    Eugene N. Muratov;Eugene N. Muratov;Jürgen Bajorath;Robert P. Sheridan;Igor V. Tetko

  • QSAR-Based Virtual Screening: Advances and Applications in Drug Discovery.

    Bruno J. Neves;Rodolpho C. Braga;Cleber C. Melo-Filho;José Teófilo Moreira-Filho

  • Materials Cartography: Representing and Mining Materials Space Using Structural and Electronic Fingerprints

    Olexandr Isayev;Denis Fourches;Eugene N. Muratov;Corey Oses

  • CERAPP: Collaborative Estrogen Receptor Activity Prediction Project

    Kamel Mansouri;Ahmed Abdelaziz;Aleksandra Rybacka;Alessandra Roncaglioni

  • Does rational selection of training and test sets improve the outcome of QSAR modeling

    Todd M. Martin;Paul Harten;Douglas M. Young;Eugene N. Muratov;Eugene N. Muratov

  • Comprehensive characterization of the Published Kinase Inhibitor Set

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

  • Trust, but Verify II: A Practical Guide to Chemogenomics Data Curation

    Denis Fourches;Eugene N. Muratov;Alexander Tropsha

  • Applicability domains for classification problems: Benchmarking of distance to models for Ames mutagenicity set.

    Iurii Sushko;Sergii Novotarskyi;Robert Körner;Anil Kumar Pandey

  • Phantom PAINS: Problems with the Utility of Alerts for Pan-Assay INterference CompoundS

    Stephen J. Capuzzi;Eugene N. Muratov;Alexander Tropsha

  • Materials Cartography: Representing and Mining Material Space Using Structural and Electronic Fingerprints

    Olexandr Isayev;Denis Fourches;Eugene N. Muratov;Corey Oses

  • Predicting Drug-induced Hepatotoxicity Using QSAR and Toxicogenomics Approaches

    Yen Low;Takeki Uehara;Yohsuke Minowa;Hiroshi Yamada

  • Pred-hERG: A Novel web-Accessible Computational Tool for Predicting Cardiac Toxicity.

    Rodolpho C. Braga;Vinicius M. Alves;Meryck F. B. Silva;Eugene Muratov

  • Curation of chemogenomics data.

    Denis Fourches;Eugene Muratov;Alexander Tropsha

  • CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity.

    Kamel Mansouri;Nicole Kleinstreuer;Ahmed M. Abdelaziz;Domenico Alberga

  • Application of Random Forest Approach to QSAR Prediction of Aquatic Toxicity

    Pavel G. Polishchuk;Eugene N. Muratov;Anatoly G. Artemenko;Oleg G. Kolumbin

  • Hierarchical QSAR technology based on the Simplex representation of molecular structure.

    Victor Kuzmin;Anatoly G. Artemenko;Eugene N. Muratov

  • A critical overview of computational approaches employed for COVID-19 drug discovery.

    Eugene N Muratov;Rommie Amaro;Carolina H Andrade;Nathan Brown

  • Progress towards a public chemogenomic set for protein kinases and a call for contributions

    David H. Drewry;Carrow I. Wells;David M. Andrews;Richard Angell

  • Data Set Modelability by QSAR

    Alexander Golbraikh;Eugene N. Muratov;Eugene N. Muratov;Denis Fourches;Alexander Tropsha

Frequent Co-Authors

Alexander Tropsha
Alexander Tropsha University of North Carolina at Chapel Hill
Denis Fourches
Denis Fourches North Carolina State University
Jerzy Leszczynski
Jerzy Leszczynski Jackson State University
Leonid Gorb
Leonid Gorb Jackson State University
Alexandre Varnek
Alexandre Varnek University of Strasbourg
Peter Wutzler
Peter Wutzler Friedrich Schiller University Jena
Anton Simeonov
Anton Simeonov National Institutes of Health
Igor V. Tetko
Igor V. Tetko Helmholtz Zentrum München
Vladimir Poroikov
Vladimir Poroikov Institute of Business & Medical Careers
Sean Ekins
Sean Ekins University of Arizona

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