World's Best Scientists 2026 revealed!

D-Index & Metrics

Biology and Biochemistry

D-Index
85
Citations
36677
World Ranking
3084
National Ranking
1560

Computer Science

D-Index
83
Citations
37607
World Ranking
886
National Ranking
484

Chemistry

D-Index
83
Citations
38076
World Ranking
2889
National Ranking
982

Alexander Tropsha 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 Alexander Tropsha 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: 276 publications — 69th percentile

69% of scientists in this discipline score the same or lower.

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

Alexander Tropsha 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 Alexander Tropsha 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: 83 D-Index — 94th percentile

94% of scientists in this discipline score the same or lower.

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

Overview

Alexander Tropsha is affiliated with the University of North Carolina at Chapel Hill in the United States. Their research primarily spans the fields of Biochemistry, Genetics and Molecular Biology, and Computer Science. The scientist's work includes significant contributions to Molecular Biology, Computational Theory and Mathematics, Infectious Diseases, Materials Chemistry, and Artificial Intelligence.

Their research topics focus heavily on computational methods in drug discovery, with broader interests encompassing bioinformatics and genomic networks, biomedical text mining and ontologies, machine learning in materials science, protein structure and dynamics, metabolomics and mass spectrometry studies, as well as analytical chemistry and chromatography.

Alexander Tropsha's recent publications include:

  • "QSAR without borders," 2020, Chemical Society Reviews
  • "The transformational role of GPU computing and deep learning in drug discovery," 2022, Nature Machine Intelligence
  • "Integrating QSAR modelling and deep learning in drug discovery: the emergence of deep QSAR," 2023, Nature Reviews Drug Discovery
  • "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

Frequent coauthors collaborating with Alexander Tropsha include Eugene Muratov, Vinícius M. Alves, Denis Fourches, Daniel Korn, and Alexey Zakharov.

Publication venues where Alexander Tropsha's work has appeared often include UNC Libraries, OPAL (Open@LaTrobe) (La Trobe University), bioRxiv (Cold Spring Harbor Laboratory), Journal of Chemical Information and Modeling, and Environmental Health Perspectives.

Alexander Tropsha has contributed to book publications, notably with the Institute of Biomedical Chemistry, Moscow, Russia eBooks. One such work is the "Abstracts of XXVII Symposium 'Bioinformatics and Computer-Aided Drug Discovery'," published in 2021.

Best Publications

  • Beware of q2

    Alexander Golbraikh;Alexander Tropsha

  • The Importance of Being Earnest: Validation is the Absolute Essential for Successful Application and Interpretation of QSPR Models

    Alexander Tropsha;Paola Gramatica;Vijay K. Gombar

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

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

  • Best Practices for QSAR Model Development, Validation, and Exploitation.

    Alexander Tropsha

  • Deep reinforcement learning for de novo drug design

    Mariya Popova;Mariya Popova;Mariya Popova;Olexandr Isayev;Alexander E Tropsha

  • Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection.

    Alexander Golbraikh;Alexander Tropsha

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

    Denis Fourches;Eugene N. Muratov;Alexander Tropsha

  • Rational selection of training and test sets for the development of validated QSAR models.

    Alexander Golbraikh;Min Shen;Zhiyan Xiao;Yun De Xiao

  • QSAR without borders

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

  • Beware of R2: Simple, Unambiguous Assessment of the Prediction Accuracy of QSAR and QSPR Models

    David L J Alexander;Alexander Tropsha;David Alan Winkler

  • Chemical Basis of Interactions Between Engineered Nanoparticles and Biological Systems

    Qingxin Mu;Guibin Jiang;Lingxin Chen;Hongyu Zhou;Hongyu Zhou

  • Universal fragment descriptors for predicting properties of inorganic crystals

    Olexandr Isayev;Corey Oses;Cormac Toher;Eric Gossett

  • Novel variable selection quantitative structure--property relationship approach based on the k-nearest-neighbor principle

    Weifan Zheng;Alexander Tropsha

  • Predictive QSAR modeling workflow, model applicability domains, and virtual screening.

    Alexander E Tropsha;Alexander Golbraikh

  • Critical Assessment of QSAR Models of Environmental Toxicity against Tetrahymena pyriformis: Focusing on Applicability Domain and Overfitting by Variable Selection

    Igor V. Tetko;Iurii Sushko;Anil Kumar Pandey;Hao Zhu

  • Autoimmunity is triggered by cPR-3(105–201), a protein complementary to human autoantigen proteinase-3

    William F Pendergraft;Gloria A Preston;Ruchir R Shah;Alexander Tropsha

  • Quantitative Nanostructure−Activity Relationship Modeling

    Denis Fourches;Dongqiuye Pu;Carlos Tassa;Ralph Weissleder

  • 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

  • Cross-validated R2-guided region selection for comparative molecular field analysis: a simple method to achieve consistent results.

    Sung Jin Cho;Alexander Tropsha

  • Combinatorial QSAR Modeling of Chemical Toxicants Tested against Tetrahymena pyriformis

    Hao Zhu;Alexander Tropsha;Denis Fourches;Alexandre Varnek

Frequent Co-Authors

Eugene N. Muratov
Eugene N. Muratov University of North Carolina at Chapel Hill
Denis Fourches
Denis Fourches North Carolina State University
Hao Zhu
Hao Zhu Rutgers, The State University of New Jersey
Olexandr Isayev
Olexandr Isayev Carnegie Mellon University
Ivan Rusyn
Ivan Rusyn Texas A&M University
Igor V. Tetko
Igor V. Tetko Helmholtz Zentrum München
Alexandre Varnek
Alexandre Varnek University of Strasbourg
Stefano Curtarolo
Stefano Curtarolo Duke University
Jan F. Prins
Jan F. Prins University of North Carolina at Chapel Hill
Jack Snoeyink
Jack Snoeyink University of North Carolina at Chapel Hill

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