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Dong-Sheng Cao

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 59 3422 3326 459 456 145 13982

Dong-Sheng Cao publications per year

The chart shows the history of publications by Dong-Sheng Cao between 2008 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Dong-Sheng Cao published across 18 years, from 2008 to 2025, averaging 16.5 papers a year. Output peaked at 43 publications in 2021. 64 of the 297 publications appeared in the last two years.

No. of publications
10 20 30 40
Bar chart. Horizontal axis: year, 2008 to 2025. Vertical axis: number of publications, 0 to 43. Peak 43 publications in 2021. 2008: 1 publication 2009: 2 publications 2010: 8 publications 2011: 12 publications 2012: 13 publications 2013: 16 publications 2014: 6 publications 2015: 10 publications 2016: 9 publications 2017: 10 publications 2018: 9 publications 2019: 12 publications 2020: 21 publications 2021: 43 publications 2022: 35 publications 2023: 26 publications 2024: 36 publications 2025: 28 publications
2008 2025

297 publications in total across all disciplines

View publications per year as a table
Dong-Sheng Cao: publications per year, 2008 to 2025
Year Publications
2008 1
2009 2
2010 8
2011 12
2012 13
2013 16
2014 6
2015 10
2016 9
2017 10
2018 9
2019 12
2020 21
2021 43
2022 35
2023 26
2024 36
2025 28
Total 297
Download as CSV

Dong-Sheng Cao 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 Dong-Sheng Cao 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, 142–151 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: 145 publications — 25th percentile

25% 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
142–151 609 145
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
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

Dong-Sheng Cao 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 Dong-Sheng Cao 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: 59 D-Index — 77th percentile

77% 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 59
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

Dong-Sheng Cao is affiliated with Central South University in China and has a significant publication record across multiple fields including biochemistry, genetics, molecular biology, and computer science. Their research spans diverse subfields such as molecular biology, computational theory and mathematics, materials chemistry, pharmacology, and organic chemistry.

The scientist's main research topics include computational drug discovery methods, machine learning applications in materials science and bioinformatics, protein structure and dynamics, bioinformatics and genomic networks, pharmacogenetics and drug metabolism, as well as microbial natural products and biosynthesis.

Frequent coauthors collaborating with Dong-Sheng Cao have been Tingjun Hou, Aiping Lü, Dejun Jiang, Chang-Yu Hsieh, and Xiangxiang Zeng. The scientist's work has appeared repeatedly in several prominent publication venues:

  • Briefings in Bioinformatics
  • Journal of Chemical Information and Modeling
  • Journal of Medicinal Chemistry
  • Journal of Cheminformatics
  • Nucleic Acids Research

Among recent notable papers authored or coauthored by Dong-Sheng Cao are:

  • "ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties," 2021, Nucleic Acids Research
  • "ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision support," 2024, Nucleic Acids Research
  • "Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models," 2021, Journal of Cheminformatics
  • "A unified drug-target interaction prediction framework based on knowledge graph and recommendation system," 2021, Nature Communications
  • "InteractionGraphNet: A Novel and Efficient Deep Graph Representation Learning Framework for Accurate Protein-Ligand Interaction Predictions," 2021, Journal of Medicinal Chemistry

Dong-Sheng Cao's work emphasizes computational methodologies for drug discovery and bioinformatics, integrating machine learning techniques to enhance predictive models and biological understanding. The research spans theoretical approaches and practical platforms, often focusing on molecular and protein-level interactions.

Best Publications

  • Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibration.

    Hongdong Li;Yizeng Liang;Qingsong Xu;Dongsheng Cao

  • ADMETlab: a platform for systematic ADMET evaluation based on a comprehensively collected ADMET database

    Jie Dong;Jie Dong;Ning-Ning Wang;Zhi-Jiang Yao;Lin Zhang

  • Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models

    Dejun Jiang;Zhenxing Wu;Chang-Yu Hsieh;Guangyong Chen

  • propy: a tool to generate various modes of Chou’s PseAAC

    Dong-Sheng Cao;Qing-Song Xu;Yi-Zeng Liang

  • An overview of variable selection methods in multivariate analysis of near-infrared spectra

    Yong-Huan Yun;Hong-Dong Li;Bai-Chuan Deng;Dong-Sheng Cao

  • TargetNet: a web service for predicting potential drug–target interaction profiling via multi-target SAR models

    Zhi-Jiang Yao;Jie Dong;Yu-Jing Che;Min-Feng Zhu

  • ChemDes: an integrated web-based platform for molecular descriptor and fingerprint computation

    Jie Dong;Dong‑Sheng Cao;Hong‑Yu Miao;Shao Liu

  • protr/ProtrWeb: R package and web server for generating various numerical representation schemes of protein sequences

    Nan Xiao;Dong-Sheng Cao;Min-Feng Zhu;Qing-Song Xu

  • ChemoPy: freely available python package for computational biology and chemoinformatics

    Dong-Sheng Cao;Qing-Song Xu;Qian-Nan Hu;Yi-Zeng Liang

  • ADME Properties Evaluation in Drug Discovery: Prediction of Caco-2 Cell Permeability Using a Combination of NSGA-II and Boosting

    Ning-Ning Wang;Jie Dong;Yin-Hua Deng;Min-Feng Zhu

  • A strategy that iteratively retains informative variables for selecting optimal variable subset in multivariate calibration.

    Yong-Huan Yun;Wei-Ting Wang;Min-Li Tan;Yi-Zeng Liang

  • A unified drug-target interaction prediction framework based on knowledge graph and recommendation system.

    Qing Ye;Chang-Yu Hsieh;Ziyi Yang;Yu Kang

  • From machine learning to deep learning: Advances in scoring functions for protein–ligand docking

    Chao Shen;Junjie Ding;Zhe Wang;Dongsheng Cao

  • An efficient method of wavelength interval selection based on random frog for multivariate spectral calibration.

    Yong-Huan Yun;Hong-Dong Li;Leslie R. E. Wood;Wei Fan

  • A bootstrapping soft shrinkage approach for variable selection in chemical modeling

    Bai-Chuan Deng;Bai-Chuan Deng;Bai-Chuan Deng;Yong-Huan Yun;Dong-Sheng Cao;Yu-Long Yin;Yu-Long Yin

  • PROTAC-DB: an online database of PROTACs.

    Gaoqi Weng;Chao Shen;Dongsheng Cao;Junbo Gao

  • Multi-constraint molecular generation based on conditional transformer, knowledge distillation and reinforcement learning

    Jike Wang;Jike Wang;Chang-Yu Hsieh;Mingyang Wang;Xiaorui Wang

  • A new strategy of outlier detection for QSAR/QSPR.

    Dong-Sheng Cao;Yi-Zeng Liang;Qing-Song Xu;Hong-Dong Li

  • Do we need different machine learning algorithms for QSAR modeling? A comprehensive assessment of 16 machine learning algorithms on 14 QSAR data sets.

    Zhenxing Wu;Minfeng Zhu;Yu Kang;Elaine Lai-Han Leung

  • PyBioMed: a python library for various molecular representations of chemicals, proteins and DNAs and their interactions.

    Jie Dong;Jie Dong;Zhi-Jiang Yao;Lin Zhang;Feijun Luo

  • Rcpi: R/Bioconductor package to generate various descriptors of proteins, compounds and their interactions

    Dong-Sheng Cao;Nan Xiao;Qing-Song Xu;Alex F. Chen

  • Model population analysis for variable selection

    Hong-Dong Li;Yi-Zeng Liang;Qing-Song Xu;Dong-Sheng Cao

  • The boosting: A new idea of building models

    Dong-Sheng Cao;Qing-Song Xu;Yi-Zeng Liang;Liang-Xiao Zhang

Frequent Co-Authors

Yi-Zeng Liang
Yi-Zeng Liang Central South University
Tingjun Hou
Tingjun Hou Zhejiang University
Qing-Song Xu
Qing-Song Xu Central South University
Aiping Lu
Aiping Lu Hong Kong Baptist University
Qinlu Lin
Qinlu Lin Central South University of Forestry and Technology
Yong Wang
Yong Wang Central South University
Jin-Ming Yang
Jin-Ming Yang University of Kentucky
Jie Chen
Jie Chen Jiangnan University
Zhiyong Liu
Zhiyong Liu University of Science and Technology Beijing
Han-Xiong Li
Han-Xiong Li City University of Hong Kong

External Links

Personal website of Dong-Sheng Cao Google Scholar page

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Best Scientists Citing Dong-Sheng Cao

Kuo-Chen Chou

Kuo-Chen Chou

The Gordon Life Science Institute

Publications: 78

Yi-Zeng Liang

Yi-Zeng Liang

Central South University

Publications: 50

Quansheng Chen

Quansheng Chen

Jiangsu University

Publications: 39

Yong He

Yong He

Zhejiang University

Publications: 30

Qing-Song Xu

Qing-Song Xu

Central South University

Publications: 25

Xuan Xiao

Xuan Xiao

Jingdezhen Ceramic Institute

Publications: 25

Hao Lin

Hao Lin

University of Electronic Science and Technology of China

Publications: 19

Wei Chen

Wei Chen

Chengdu University of Traditional Chinese Medicine

Publications: 19

Wensheng Cai

Wensheng Cai

Nankai University

Publications: 18

Da-Wen Sun

Da-Wen Sun

University College Dublin

Publications: 17

Xiaoli Li

Xiaoli Li

Singapore University of Technology and Design

Publications: 16

Bin Liu

Bin Liu

National University of Singapore

Publications: 16

Jijun Tang

Jijun Tang

University of South Carolina

Publications: 15

Maqsood Hayat

Maqsood Hayat

Abdul Wali Khan University Mardan

Publications: 15

Yaser Daanial Khan

Yaser Daanial Khan

University of Management and Technology

Publications: 13

Jiangning Song

Jiangning Song

Monash University

Publications: 12

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