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Daisuke Kihara

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 58 3695 3591 1763 1700 266 10721

Daisuke Kihara publications per year

The chart shows the history of publications by Daisuke Kihara between 1997 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Daisuke Kihara published across 29 years, from 1997 to 2025, averaging 15.8 papers a year. Output peaked at 54 publications in 2021. 74 of the 459 publications appeared in the last two years.

No. of publications
10 20 30 40 50
Bar chart. Horizontal axis: year, 1997 to 2025. Vertical axis: number of publications, 0 to 54. Peak 54 publications in 2021. 1997: 1 publication 1998: 1 publication 1999: 0 publications 2000: 2 publications 2001: 7 publications 2002: 2 publications 2003: 3 publications 2004: 2 publications 2005: 2 publications 2006: 5 publications 2007: 6 publications 2008: 10 publications 2009: 11 publications 2010: 8 publications 2011: 18 publications 2012: 15 publications 2013: 14 publications 2014: 15 publications 2015: 12 publications 2016: 15 publications 2017: 23 publications 2018: 29 publications 2019: 36 publications 2020: 25 publications 2021: 54 publications 2022: 36 publications 2023: 33 publications 2024: 35 publications 2025: 39 publications
1997 2025

459 publications in total across all disciplines

View publications per year as a table
Daisuke Kihara: publications per year, 1997 to 2025
Year Publications
1997 1
1998 1
1999 0
2000 2
2001 7
2002 2
2003 3
2004 2
2005 2
2006 5
2007 6
2008 10
2009 11
2010 8
2011 18
2012 15
2013 14
2014 15
2015 12
2016 15
2017 23
2018 29
2019 36
2020 25
2021 54
2022 36
2023 33
2024 35
2025 39
Total 459
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Daisuke Kihara 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 Daisuke Kihara sits on this spectrum.

No. of scientists
200 400 600
Bar chart with 97 bars. Horizontal axis: publications, 32–41 to 991+. Vertical axis: number of scientists, 0 to 609. Most scientists, 609, have 142–151 publications. The last bar groups every scientist with 991 publications or more. The highlighted bar, 262–271 publications, is where this scientist sits. 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
32–41 publications 991+

This scientist: 266 publications — 66th percentile

66% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Computer Science scientists by publication count, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
Publications Scientists This scientist
32–41 7
42–51 22
52–61 82
62–71 134
72–81 249
82–91 324
92–101 421
102–111 420
112–121 497
122–131 544
132–141 555
142–151 609
152–161 559
162–171 534
172–181 556
182–191 583
192–201 519
202–211 508
212–221 490
222–231 437
232–241 423
242–251 408
252–261 377
262–271 301 266
272–281 335
282–291 320
292–301 293
302–311 250
312–321 238
322–331 206
332–341 209
342–351 208
352–361 162
362–371 176
372–381 127
382–391 158
392–401 128
402–411 104
412–421 94
422–431 99
432–441 83
442–451 108
452–461 73
462–471 77
472–481 69
482–491 84
492–501 62
502–511 54
512–521 57
522–531 51
532–541 51
542–551 32
552–561 38
562–571 28
572–581 43
582–591 33
592–601 41
602–611 32
612–621 28
622–631 25
632–641 27
642–651 17
652–661 20
662–671 17
672–681 15
682–691 14
692–701 21
702–711 13
712–721 12
722–731 19
732–741 14
742–751 12
752–761 10
762–771 10
772–781 11
782–791 10
792–801 11
802–811 8
812–821 8
822–831 7
832–841 11
842–851 10
852–861 5
862–871 9
872–881 4
882–891 6
892–901 3
902–911 6
912–921 3
922–931 2
932–941 2
942–951 2
952–961 3
962–971 3
972–981 3
982–990 5
991+ 100
Download as CSV

Daisuke Kihara 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 Daisuke Kihara sits on this spectrum.

No. of scientists
200 400 600 800
Bar chart with 52 bars. Horizontal axis: D-Index, 30–31 to 131+. Vertical axis: number of scientists, 0 to 990. Most scientists, 990, have 36–37 D-Index. The last bar groups every scientist with 131 D-Index or more. The highlighted bar, 58–59 D-Index, is where this scientist sits. 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
30–31 D-Index 131+

This scientist: 58 D-Index — 75th percentile

75% of scientists in this discipline score the same or lower.

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

View D-Index distribution as a table
Number of Computer Science scientists by D-index, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
D-Index Scientists This scientist
30–31 879
32–33 983
34–35 918
36–37 990
38–39 968
40–41 907
42–43 821
44–45 763
46–47 689
48–49 543
50–51 543
52–53 518
54–55 500
56–57 458
58–59 400 58
60–61 337
62–63 308
64–65 292
66–67 249
68–69 213
70–71 192
72–73 189
74–75 165
76–77 139
78–79 119
80–81 121
82–83 113
84–85 88
86–87 87
88–89 75
90–91 69
92–93 57
94–95 46
96–97 38
98–99 34
100–101 36
102–103 27
104–105 37
106–107 18
108–109 31
110–111 19
112–113 16
114–115 12
116–117 20
118–119 15
120–121 5
122–123 20
124–125 8
126–127 5
128–129 7
130 3
131+ 98
Download as CSV

Overview

Daisuke Kihara is affiliated with Purdue University West Lafayette in the United States and has contributed extensively to the field of biochemistry, genetics, and molecular biology. Their research primarily focuses on the molecular biology and structural biology subfields, with significant involvement in materials chemistry, computational theory and mathematics, and computer vision and pattern recognition.

The scientist's work covers several main topics, including protein structure and dynamics, enzyme structure and function, advanced electron microscopy techniques and applications, RNA and protein synthesis mechanisms, machine learning in bioinformatics, genomics and phylogenetic studies, and computational drug discovery methods.

Frequent publication venues for Daisuke Kihara include:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Biophysical Journal
  • Methods in molecular biology
  • arXiv (Cornell University)

Among recent papers, several notable publications are:

  • Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment, 2021, Proteins Structure Function and Bioinformatics
  • Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge, 2021, Nature Methods
  • LZerD webserver for pairwise and multiple protein-protein docking, 2021, Nucleic Acids Research
  • Protein folds vs. protein folding: Differing questions, different challenges, 2022, Proceedings of the National Academy of Sciences
  • Protein Docking Model Evaluation by Graph Neural Networks, 2021, Frontiers in Molecular Biosciences

Daisuke Kihara has collaborated frequently with several coauthors, including:

  • Genki Terashi
  • Xiao Wang
  • Charles Christoffer
  • Yuki Kagaya
  • Tunde Aderinwale

Best Publications

  • A large-scale evaluation of computational protein function prediction

    Predrag Radivojac;Wyatt T Clark;Tal Ronnen Oron;Alexandra M Schnoes

  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur

  • The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

    Naihui Zhou;Yuxiang Jiang;Timothy R. Bergquist;Alexandra J. Lee

  • Limitations and potentials of current motif discovery algorithms

    Jianjun Hu;Bin Li;Daisuke Kihara

  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T Clark;Asma R Bankapur

  • Protein-protein docking using region-based 3D Zernike descriptors

    Vishwesh Venkatraman;Yifeng D Yang;Lee Sael;Daisuke Kihara

  • Development and large scale benchmark testing of the PROSPECTOR_3 threading algorithm.

    Jeffrey Skolnick;Daisuke Kihara;Yang Zhang

  • Local energy landscape flattening: parallel hyperbolic Monte Carlo sampling of protein folding.

    Yang Zhang;Daisuke Kihara;Jeffrey Skolnick

  • Enhanced automated function prediction using distantly related sequences and contextual association by PFP

    Troy Hawkins;Stanislav Luban;Daisuke Kihara

  • Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment.

    Marc F. Lensink;Sameer Velankar;Andriy Kryshtafovych;Shen You Huang

  • PFP: Automated prediction of gene ontology functional annotations with confidence scores using protein sequence data

    Troy Hawkins;Meghana Chitale;Stanislav Luban;Daisuke Kihara

  • Defrosting the frozen approximation: PROSPECTOR--a new approach to threading.

    Jeffrey Skolnick;Daisuke Kihara

  • Community-wide assessment of protein-interface modeling suggests improvements to design methodology

    Sarel J. Fleishman;Sarel J. Fleishman;Timothy A. Whitehead;Eva Maria Strauch;Jacob E. Corn;Jacob E. Corn

  • Fast protein tertiary structure retrieval based on global surface shape similarity.

    Lee Sael;Bin Li;David La;Yi Fang

  • De novo main-chain modeling for EM maps using MAINMAST

    Genki Terashi;Daisuke Kihara

  • Function prediction of uncharacterized proteins.

    Troy Hawkins;Daisuke Kihara

  • Blind prediction of homo- and hetero-protein complexes: The CASP13-CAPRI experiment.

    Marc F. Lensink;Guillaume Brysbaert;Nurul Nadzirin;Sameer Velankar

  • ESG: Extended Similarity Group method for automated protein function prediction

    Meghana Chitale;Troy Hawkins;Changsoon Park;Daisuke Kihara

  • ESG: extended similarity group method for automated protein function prediction

    Meghana Chitale;Troy Hawkins;Changsoon Park;Daisuke Kihara

  • Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment.

    Marc F Lensink;Guillaume Brysbaert;Théo Mauri;Nurul Nadzirin

  • Potential for Protein Surface Shape Analysis Using Spherical Harmonics and 3D Zernike Descriptors

    Vishwesh Venkatraman;Lee Sael;Daisuke Kihara

  • Protein docking model evaluation by 3D deep convolutional neural networks.

    Xiao Wang;Genki Terashi;Charles W Christoffer;Mengmeng Zhu

  • Additional file 1 of An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur

Frequent Co-Authors

Andrzej Kolinski
Andrzej Kolinski University of Warsaw
Jeffrey Skolnick
Jeffrey Skolnick Georgia Institute of Technology
Jianlin Cheng
Jianlin Cheng University of Missouri
Christophe Dessimoz
Christophe Dessimoz University College London
Juan Fernández-Recio
Juan Fernández-Recio Spanish National Research Council
Shoshana J. Wodak
Shoshana J. Wodak Vrije Universiteit Brussel
David T. Jones
David T. Jones University College London
Tapio Salakoski
Tapio Salakoski University of Turku
Paul A. Bates
Paul A. Bates The Francis Crick Institute
Brian G. Pierce
Brian G. Pierce University of Maryland, College Park

External Links

Personal website of Daisuke Kihara Google Scholar page

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Best Scientists Citing Daisuke Kihara

Jeffrey Skolnick

Jeffrey Skolnick

Georgia Institute of Technology

Publications: 87

Yang Zhang

Yang Zhang

University of Michigan–Ann Arbor

Publications: 72

Andrzej Kolinski

Andrzej Kolinski

University of Warsaw

Publications: 45

Christine A. Orengo

Christine A. Orengo

University College London

Publications: 39

Yaoqi Zhou

Yaoqi Zhou

Griffith University

Publications: 35

Burkhard Rost

Burkhard Rost

Technical University of Munich

Publications: 27

Alexandre M. J. J. Bonvin

Alexandre M. J. J. Bonvin

Utrecht University

Publications: 27

Vladimir N. Uversky

Vladimir N. Uversky

University of South Florida

Publications: 25

David Baker

David Baker

University of Washington

Publications: 24

Jinbo Xu

Jinbo Xu

Toyota Technological Institute at Chicago

Publications: 24

Juan Fernández-Recio

Juan Fernández-Recio

Spanish National Research Council

Publications: 23

Adam Liwo

Adam Liwo

University of Gdańsk

Publications: 21

David T. Jones

David T. Jones

University College London

Publications: 21

Lukasz Kurgan

Lukasz Kurgan

Virginia Commonwealth University

Publications: 21

Jianlin Cheng

Jianlin Cheng

University of Missouri

Publications: 21

Yuedong Yang

Yuedong Yang

Sun Yat-sen University

Publications: 19

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