World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
85
Citations
24043
World Ranking
814
National Ranking
124

Yi Pan 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 Yi Pan 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: 726 publications — 98th percentile

98% of scientists in this discipline score the same or lower.

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

Yi Pan 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 Yi Pan 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: 85 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

Yi Pan is affiliated with the Shenzhen Institutes of Advanced Technology in China. Their research spans multiple fields, primarily within computer science and biochemistry, genetics, and molecular biology. The scientist's work integrates computational methods and bioinformatics with a focus on molecular biology and cancer research.

The main fields of study of Yi Pan encompass:

  • Computer Science
  • Biochemistry, Genetics and Molecular Biology

The subfields of study include:

  • Molecular Biology
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computational Theory and Mathematics
  • Cancer Research

Yi Pan's research topics highlight a combination of computational and biological themes. Significant areas of focus are:

  • Computational Drug Discovery Methods
  • Bioinformatics and Genomic Networks
  • Circular RNAs in diseases
  • Cancer-related molecular mechanisms research
  • MicroRNA in disease regulation
  • Machine Learning in Bioinformatics
  • IoT and Edge/Fog Computing

Among Yi Pan's recent papers are:

  • Artificial intelligence in cancer target identification and drug discovery, 2022, Signal Transduction and Targeted Therapy
  • Generative Adversarial Networks, 2021, ACM Computing Surveys
  • Deep Learning Based Drug Screening for Novel Coronavirus 2019-nCov, 2020, Interdisciplinary Sciences Computational Life Sciences
  • Variational Few-Shot Learning for Microservice-Oriented Intrusion Detection in Distributed Industrial IoT, 2021, IEEE Transactions on Industrial Informatics
  • Gradient amplification: An efficient way to train deep neural networks, 2020, Big Data Mining and Analytics

Yi Pan frequently collaborates with several co-authors, including:

  • Xiujuan Lei
  • Yanjie Wei
  • Chunyan Ji
  • Haiping Zhang
  • Jong Hyuk Park

The scholar publishes regularly in select venues, with notable frequency in:

  • arXiv (Cornell University)
  • IEEE/ACM Transactions on Computational Biology and Bioinformatics
  • Big Data Mining and Analytics
  • Briefings in Bioinformatics
  • Journal of Computer Science and Technology

Yi Pan has also contributed to several books published by Springer Science+Business Media, including:

  • Advances in Computer Science and Ubiquitous Computing (2021)
  • Advances in Computer Science and Ubiquitous Computing (2023)
  • Computer Networks and IoT (2024)
  • Artificial Intelligence and Mobile Services - AIMS 2021 (2022)

Best Publications

  • CytoNCA: a cytoscape plugin for centrality analysis and evaluation of protein interaction networks.

    Yu Tang;Min Li;Jianxin Wang;Yi Pan

  • A survey of MRI-based brain tumor segmentation methods

    Jin Liu;Min Li;Jianxin Wang;Fangxiang Wu

  • A study of the routing and spectrum allocation in spectrum-sliced Elastic Optical Path networks

    Yang Wang;Xiaojun Cao;Yi Pan

  • Drug repositioning based on comprehensive similarity measures and Bi-Random walk algorithm

    Huimin Luo;Jianxin Wang;Min Li;Junwei Luo

  • Identification of Essential Proteins Based on Edge Clustering Coefficient

    Jianxin Wang;Min Li;Huan Wang;Yi Pan

  • An improved method for forecasting enrollments based on fuzzy time series and particle swarm optimization

    I-Hong Kuo;Shi-Jinn Horng;Tzong-Wann Kao;Tsung-Lieh Lin

  • Generative Adversarial Networks: A Survey Toward Private and Secure Applications

    Zhipeng Cai;Zuobin Xiong;Honghui Xu;Peng Wang

  • b-SPECS+: Batch Verification for Secure Pseudonymous Authentication in VANET

    Shi-Jinn Horng;Shiang-Feng Tzeng;Yi Pan;Pingzhi Fan

  • Applications of Deep Learning to MRI Images: A Survey

    Jin Liu;Yi Pan;Min Li;Ziyue Chen

  • An Efficient Watermarking Method Based on Significant Difference of Wavelet Coefficient Quantization

    Wei-Hung Lin;Shi-Jinn Horng;Tzong-Wann Kao;Pingzhi Fan

  • A new essential protein discovery method based on the integration of protein-protein interaction and gene expression data

    Min Li;Min Li;Hanhui Zhang;Jian-xin Wang;Yi Pan;Yi Pan

  • Prediction of lncRNA-disease associations based on inductive matrix completion.

    Chengqian Lu;Mengyun Yang;Feng Luo;Fang-Xiang Wu

  • A Fast Hierarchical Clustering Algorithm for Functional Modules Discovery in Protein Interaction Networks

    Jianxin Wang;Min Li;Jianer Chen;Yi Pan

  • Classification of autism spectrum disorder by combining brain connectivity and deep neural network classifier

    Yazhou Kong;Jianliang Gao;Yunpei Xu;Yi Pan;Yi Pan

  • Parallel granular neural networks for fast credit card fraud detection

    M. Syeda;Yan-Qing Zhang;Yi Pan

  • Predicting essential proteins based on weighted degree centrality

    Xiwei Tang;Jianxin Wang;Jiancheng Zhong;Yi Pan

  • A local average connectivity-based method for identifying essential proteins from the network level

    Min Li;Jianxin Wang;Xiang Chen;Huan Wang

  • Classification of Alzheimer's Disease Using Whole Brain Hierarchical Network

    Jin Liu;Min Li;Wei Lan;Fang-Xiang Wu

  • LDAP: a web server for lncRNA-disease association prediction

    Wei Lan;Min Li;Kaijie Zhao;Jin Liu

  • Comparative analysis of quality of service and memory usage for adaptive failure detectors in healthcare systems

    Naixue Xiong;A. Vasilakos;L. Yang;Lingyang Song

  • An Efficient Watermarking Method Based on Significant Difference of

    Wei-Hung Lin;Shi-Jinn Horng;Tzong-Wann Kao;Pingzhi Fan

Frequent Co-Authors

Jianxin Wang
Jianxin Wang Central South University
Min Li
Min Li Central South University
Fang-Xiang Wu
Fang-Xiang Wu University of Saskatchewan
Keqin Li
Keqin Li State University of New York at New Paltz
Robert J. Harrison
Robert J. Harrison Murdoch University
Phang C. Tai
Phang C. Tai Georgia State University
Yang Xiao
Yang Xiao University of Alabama
Tianrui Li
Tianrui Li Southwest Jiaotong University
Jong Hyuk Park
Jong Hyuk Park Seoul National University of Science and Technology
Pingzhi Fan
Pingzhi Fan Southwest Jiaotong University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring Computer Science opens up many options for flexible online learning and diverse career paths in the USA. If you’re considering advanced education, understanding which master's degree is most in demand in usa can help you choose programs with strong job prospects and high earning potential.

You don’t have to start with a bachelor’s degree—many students begin with online associate degree programs in computer science or IT to build foundational skills. These programs are usually shorter and more affordable, providing a stepping stone to further studies or entry-level jobs.

For those concerned about costs, there are plenty of affordable online courses available across the country. These options allow you to learn flexibly while saving money on tuition and other expenses.

Academic history doesn’t have to limit your options. Several college that accepts low gpa offer computer science programs, making this field accessible to students from diverse educational backgrounds.

Best Scientists Citing Yi Pan

Trending Scientists

Recently Published Articles