World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
88
Citations
23829
World Ranking
696
National Ranking
104

Quan Zou 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 Quan Zou 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: 368 publications — 84th percentile

84% of scientists in this discipline score the same or lower.

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

Quan Zou 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 Quan Zou 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: 88 D-Index — 95th percentile

95% 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

  • 2015 - ACM Senior Member

Overview

Quan Zou is affiliated with the University of Electronic Science and Technology of China. Their research primarily focuses on the broad field of Biochemistry, Genetics and Molecular Biology, with specialized work in Molecular Biology, Cancer Research, Computational Theory and Mathematics, Artificial Intelligence, and Microbiology.

The scientist's publication record includes numerous articles in prominent journals, with a strong presence in venues such as Briefings in Bioinformatics, Bioinformatics, BMC Biology, PLoS Computational Biology, and the IEEE Journal of Biomedical and Health Informatics.

Quan Zou's most recent papers include the following:

  • "webTWAS: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study," 2021, Nucleic Acids Research
  • "Distance-based Support Vector Machine to Predict DNA N6-methyladenine Modification," 2022, Current Bioinformatics
  • "SBSM-Pro: support bio-sequence machine for proteins," 2024, Science China Information Sciences
  • "DeepBIO: an automated and interpretable deep-learning platform for high-throughput biological sequence prediction, functional annotation and visualization analysis," 2023, Nucleic Acids Research
  • "Molecular design in drug discovery: a comprehensive review of deep generative models," 2021, Briefings in Bioinformatics

Frequent coauthors in their collaborative network include Feifei Cui, Yijie Ding, Leyi Wei, Zilong Zhang, and Fei Guo.

The main topics Quan Zou works on comprise:

  • Machine Learning in Bioinformatics
  • RNA and protein synthesis mechanisms
  • Genomics and Phylogenetic Studies
  • Computational Drug Discovery Methods
  • Bioinformatics and Genomic Networks
  • Single-cell and spatial transcriptomics
  • Cancer-related molecular mechanisms research

They have been recognized with the ACM Senior Member award since 2015.

Best Publications

  • Predicting Diabetes Mellitus With Machine Learning Techniques

    Unknown

  • Biological functions of microRNAs: a review

    Yong Huang;Xing Jia Shen;Quan Zou;Sheng Peng Wang

  • Gene2vec: gene subsequence embedding for prediction of mammalian N6-methyladenosine sites from mRNA.

    Quan Zou;Quan Zou;Pengwei Xing;Leyi Wei;Bin Liu

  • A novel features ranking metric with application to scalable visual and bioinformatics data classification

    Quan Zou;Jiancang Zeng;Liujuan Cao;Rongrong Ji

  • A comprehensive overview and evaluation of circular RNA detection tools.

    Xiangxiang Zeng;Wei Lin;Maozu Guo;Quan Zou

  • webTWAS: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study.

    Chen Cao;Jianhua Wang;Devin Kwok;Feifei Cui

  • Integrative approaches for predicting microRNA function and prioritizing disease-related microRNA using biological interaction networks

    Xiangxiang Zeng;Xuan Zhang;Quan Zou

  • Tumor origin detection with tissue-specific miRNA and DNA methylation markers.

    Wei Tang;Shixiang Wan;Zhen Yang;Andrew E Teschendorff;Andrew E Teschendorff

  • Inferring MicroRNA-Disease Associations by Random Walk on a Heterogeneous Network with Multiple Data Sources

    Yuansheng Liu;Xiangxiang Zeng;Zengyou He;Quan Zou

  • Finding the Best Classification Threshold in Imbalanced Classification

    Quan Zou;Quan Zou;Sifa Xie;Ziyu Lin;Meihong Wu

  • LibD3C: Ensemble classifiers with a clustering and dynamic selection strategy

    Chen Lin;Wenqiang Chen;Cheng Qiu;Yunfeng Wu

  • Similarity computation strategies in the microRNA-disease network: a survey

    Quan Zou;Jinjin Li;Li Song;Xiangxiang Zeng

  • Local-DPP: An improved DNA-binding protein prediction method by exploring local evolutionary information

    Leyi Wei;Jijun Tang;Jijun Tang;Quan Zou

  • Improved and promising identification of human MicroRNAs by incorporating a high-quality negative set

    Leyi Wei;Minghong Liao;Yue Gao;Rongrong Ji

  • Prediction of potential disease-associated microRNAs using structural perturbation method.

    Xiangxiang Zeng;Li Liu;Linyuan Lü;Quan Zou

  • Survey of MapReduce frame operation in bioinformatics

    Quan Zou;Xu-Bin Li;Wen-Rui Jiang;Zi-Yu Lin

  • Prediction of human protein subcellular localization using deep learning

    Leyi Wei;Leyi Wei;Yijie Ding;Ran Su;Ran Su;Jijun Tang

  • Deep-Resp-Forest: A deep forest model to predict anti-cancer drug response

    Ran Su;Xinyi Liu;Leyi Wei;Quan Zou

  • Sequence clustering in bioinformatics: an empirical study.

    Quan Zou;Quan Zou;Gang Lin;Xingpeng Jiang;Xiangrong Liu

  • Prediction and Validation of Disease Genes Using HeteSim Scores

    Xiangxiang Zeng;Yuanlu Liao;Yuansheng Liu;Quan Zou

  • Fast Prediction of Protein Methylation Sites Using a Sequence-Based Feature Selection Technique

    Leyi Wei;Pengwei Xing;Gaotao Shi;Zhiliang Ji

Frequent Co-Authors

Xiangxiang Zeng
Xiangxiang Zeng Hunan University
Leyi Wei
Leyi Wei Shandong University
Maozu Guo
Maozu Guo Beijing University of Civil Engineering and Architecture
Jijun Tang
Jijun Tang University of South Carolina
Ran Su
Ran Su Tianjin University
Qinghua Hu
Qinghua Hu Tianjin University
Xiangke Liao
Xiangke Liao National University of Defense Technology
Rongrong Ji
Rongrong Ji Xiamen University
Xiaolong Wang
Xiaolong Wang University of California, San Diego
Qin Ma
Qin Ma The Ohio State University

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