World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
56
Citations
16040
World Ranking
4002
National Ranking
1907

Jinbo Xu 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 Jinbo Xu 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: 168 publications — 34th percentile

34% of scientists in this discipline score the same or lower.

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

Jinbo Xu 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 Jinbo Xu 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: 56 D-Index — 72nd percentile

72% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2012 - Fellow of Alfred P. Sloan Foundation

Overview

Jinbo Xu is affiliated with the Toyota Technological Institute at Chicago in the United States. Their research primarily spans biochemistry, genetics, and molecular biology with a focus on molecular biology as the main subfield, alongside contributions to materials chemistry, genetics, ecology, and computer vision and pattern recognition.

Their scholarly output includes numerous recent publications covering topics such as protein structure and dynamics, machine learning in bioinformatics, enzyme structure and function, genomics and phylogenetic studies, RNA and protein synthesis mechanisms, vaccines and immunoinformatics approaches, and bioinformatics and genomic networks.

Frequent co-authors of Jinbo Xu include Ben Lai, Matt McPartlon, Xiaoyang Jing, Fandi Wu, and Xiao-Lei Wu, indicating collaboration within a focused research community.

Key publication venues where Jinbo Xu has contributed include bioRxiv (Cold Spring Harbor Laboratory), Zenodo (CERN European Organization for Nuclear Research), Bioinformatics, Briefings in Bioinformatics, and Proceedings of the National Academy of Sciences.

Notable recent papers involving Jinbo Xu are:

  • Improved protein structure prediction by deep learning irrespective of co-evolution information (2021, Nature Machine Intelligence)
  • Critical assessment of protein intrinsic disorder prediction (2021, Nature Methods)
  • The landscape of tolerated genetic variation in humans and primates (2023, Science)
  • Accurate protein function prediction via graph attention networks with predicted structure information (2021, Briefings in Bioinformatics)
  • Deep graph learning of inter-protein contacts (2021, Bioinformatics)

Jinbo Xu's research often integrates advanced computational techniques such as deep learning and graph networks applied to protein-related problems, supporting advances in structure prediction and function annotation.

In 2012, Jinbo Xu was recognized as a Fellow of the Alfred P. Sloan Foundation, an award acknowledging contributions to their field.

Best Publications

  • Opportunities and obstacles for deep learning in biology and medicine.

    Travers Ching;Daniel S. Himmelstein;Brett K. Beaulieu-Jones;Alexandr A. Kalinin

  • Template-based protein structure modeling using the RaptorX web server

    Morten Källberg;Morten Källberg;Haipeng Wang;Sheng Wang;Jian Peng

  • Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model.

    Sheng Wang;Siqi Sun;Zhen Li;Renyu Zhang

  • Global alignment of multiple protein interaction networks with application to functional orthology detection.

    Rohit Singh;Jinbo Xu;Bonnie Berger

  • Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields.

    Sheng Wang;Jian Peng;Jianzhu Ma;Jinbo Xu

  • RaptorX-Property: a web server for protein structure property prediction.

    Sheng Wang;Wei Li;Shiwang Liu;Jinbo Xu

  • Predicting the clinical impact of human mutation with deep neural networks

    Laksshman Sundaram;Laksshman Sundaram;Laksshman Sundaram;Hong Gao;Samskruthi Reddy Padigepati;Samskruthi Reddy Padigepati;Jeremy F. McRae

  • Raptorx: Exploiting structure information for protein alignment by statistical inference

    Jian Peng;Jinbo Xu

  • Distance-based protein folding powered by deep learning.

    Jinbo Xu

  • Pairwise global alignment of protein interaction networks by matching neighborhood topology

    Rohit Singh;Jinbo Xu;Bonnie Berger

  • Predicting protein-protein interactions through sequence-based deep learning.

    Somaye Hashemifar;Behnam Neyshabur;Aly A Khan;Jinbo Xu

  • RAPTOR: optimal protein threading by linear programming.

    Jinbo Xu;Ming Li;Dongsup Kim;Ying Xu

  • RaptorX server: a resource for template-based protein structure modeling.

    Morten Källberg;Gohar Margaryan;Sheng Wang;Jianzhu Ma

  • Improved protein structure prediction by deep learning irrespective of co-evolution information

    Jinbo Xu;Matthew McPartlon;Matthew McPartlon;Jin Li;Jin Li

  • Conditional Neural Fields

    Jian Peng;Liefeng Bo;Jinbo Xu

  • Protein structure alignment beyond spatial proximity

    Sheng Wang;Jianzhu Ma;Jian Peng;Jinbo Xu

  • Struct2Net: a web service to predict protein–protein interactions using a structure-based approach

    Rohit Singh;Daniel Kyu Park;Jinbo Xu;Raghavendra Hosur

  • Protein threading using context-specific alignment potential

    Jianzhu Ma;Sheng Wang;Feng Zhao;Jinbo Xu

  • Predicting protein contact map using evolutionary and physical constraints by integer programming

    Zhiyong Wang;Jinbo Xu

  • Analysis of distance-based protein structure prediction by deep learning in CASP13

    Jinbo Xu;Sheng Wang

  • Protein structure alignment beyond spatial proximity

    Sheng Wang;Jianzhu Ma;Jian Peng;Jinbo Xu

Frequent Co-Authors

Jian Peng
Jian Peng University of Illinois at Urbana-Champaign
Xin Gao
Xin Gao King Abdullah University of Science and Technology
Yizhou Yu
Yizhou Yu University of Hong Kong
Karl F. Freed
Karl F. Freed University of Chicago
Tobin R. Sosnick
Tobin R. Sosnick University of Chicago
Anne E. Carpenter
Anne E. Carpenter Broad Institute
Inna Dubchak
Inna Dubchak Lawrence Berkeley National Laboratory
Ying Xu
Ying Xu University of Georgia
Anshul Kundaje
Anshul Kundaje Stanford University

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