World's Best Scientists 2026 revealed!

D-Index & Metrics

Biology and Biochemistry

D-Index
68
Citations
17252
World Ranking
7761
National Ranking
244

Computer Science

D-Index
66
Citations
16864
World Ranking
2336
National Ranking
322

Xing Chen 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 Xing Chen 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: 135 publications — 21st percentile

21% of scientists in this discipline score the same or lower.

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

Xing Chen 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 Xing Chen 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: 66 D-Index — 84th percentile

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

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

Overview

Xing Chen is affiliated with Jiangnan University in China and has an extensive publication record primarily in the fields of Biochemistry, Genetics and Molecular Biology, as well as Medicine. Their research focuses on molecular biology, cancer research, computational theory and mathematics, oncology, and molecular medicine.

The scientist's recent notable papers include:

  • Deep-belief network for predicting potential miRNA-disease associations, 2020, published in Briefings in Bioinformatics
  • Prediction of potential miRNA-disease associations based on stacked autoencoder, 2022, published in Briefings in Bioinformatics

Xing Chen has collaborated frequently with several researchers including Chun-Chun Wang, Guanghua Zhang, Feifan Hou, Lihong Peng, and Junfeng Zhu. These collaborations have contributed to a range of publications in prominent venues.

Their articles have appeared regularly in journals such as:

  • Briefings in Bioinformatics
  • Computers in Biology and Medicine
  • IEEE Journal of Biomedical and Health Informatics
  • International Journal of Biological Macromolecules
  • International Immunopharmacology

Xing Chen's research covers numerous main topics, particularly in areas involving computational and biological methods, including:

  • Computational Drug Discovery Methods
  • Bioinformatics and Genomic Networks
  • Cancer-related molecular mechanisms research
  • MicroRNA in disease regulation
  • Circular RNAs in diseases
  • Single-cell and spatial transcriptomics
  • Machine Learning in Bioinformatics

With a substantial number of publications, Xing Chen's work frequently explores the intersection of machine learning and bioinformatics to address complex biological and medical problems. They have contributed specifically to the study of microRNA associations with diseases and the computational modeling of drug-target interactions.

Best Publications

  • LncRNADisease: a database for long-non-coding RNA-associated diseases

    Geng Chen;Ziyun Wang;Dongqing Wang;Chengxiang Qiu

  • Drug–target interaction prediction: databases, web servers and computational models

    Xing Chen;Chenggang Clarence Yan;Xiaotian Zhang;Xu Zhang

  • Novel human lncRNA-disease association inference based on lncRNA expression profiles

    Xing Chen;Gui-Ying Yan

  • MicroRNAs and complex diseases: from experimental results to computational models.

    Xing Chen;Di Xie;Qi Zhao;Zhu-Hong You

  • Long non-coding RNAs and complex diseases: from experimental results to computational models

    Xing Chen;Chenggang Clarence Yan;Xu Zhang;Zhu-Hong You

  • Drug-target interaction prediction by random walk on the heterogeneous network.

    Xing Chen;Ming-Xi Liu;Gui-Ying Yan

  • RWRMDA: predicting novel human microRNA–disease associations

    Xing Chen;Ming-Xi Liu;Gui-Ying Yan

  • Predicting miRNA-disease association based on inductive matrix completion.

    Xing Chen;Lei Wang;Jia Qu;Na-Na Guan

  • Semi-supervised learning for potential human microRNA-disease associations inference

    Xing Chen;Gui-Ying Yan

  • PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction.

    Zhu-Hong You;Zhi-An Huang;Zexuan Zhu;Gui-Ying Yan

  • WBSMDA: Within and Between Score for MiRNA-Disease Association prediction.

    Xing Chen;Chenggang Clarence Yan;Xu Zhang;Zhu Hong You

  • MDHGI: Matrix Decomposition and Heterogeneous Graph Inference for miRNA-disease association prediction.

    Xing Chen;Jun Yin;Jia Qu;Li Huang

  • The B-RafV600E inhibitor dabrafenib selectively inhibits RIP3 and alleviates acetaminophen-induced liver injury

    Li Jx;Feng Jm;Wang Y;Li Xh

  • BNPMDA: Bipartite Network Projection for MiRNA-Disease Association prediction.

    Xing Chen;Di Xie;Lei Wang;Qi Zhao

  • EGBMMDA: Extreme Gradient Boosting Machine for MiRNA-Disease Association prediction.

    Xing Chen;Li Huang;Di Xie;Qi Zhao

  • NLLSS: Predicting Synergistic Drug Combinations Based on Semi-supervised Learning.

    Xing Chen;Biao Ren;Ming Chen;Quanxin Wang

  • Constructing lncRNA functional similarity network based on lncRNA-disease associations and disease semantic similarity

    Xing Chen;Chenggang Clarence Yan;Cai Luo;Wen Ji

  • A novel approach based on KATZ measure to predict associations of human microbiota with non-infectious diseases

    Xing Chen;Yu-An Huang;Zhu-Hong You;Gui-Ying Yan

  • HGIMDA: Heterogeneous graph inference for miRNA-disease association prediction

    Xing Chen;Chenggang Clarence Yan;Xu Zhang;Zhu-Hong You

  • LRSSLMDA: Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction.

    Xing Chen;Li Huang

Frequent Co-Authors

Zhu-Hong You
Zhu-Hong You Chinese Academy of Sciences
Jianqiang Li
Jianqiang Li Beijing University of Technology
Zexuan Zhu
Zexuan Zhu Shenzhen University
De-Shuang Huang
De-Shuang Huang Tongji University
Yongdong Zhang
Yongdong Zhang University of Science and Technology of China
Hui Liu
Hui Liu China University of Mining and Technology
Qionghai Dai
Qionghai Dai Tsinghua University
Keith C. C. Chan
Keith C. C. Chan Hong Kong Polytechnic University
Qinghua Cui
Qinghua Cui Peking University
Lixin Zhang
Lixin Zhang East China University of Science and Technology

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 online study options can open flexible and affordable pathways into computer science and related fields. Many students start with an associate degree online, which can provide a solid foundation in programming and IT basics—often in as little as six months.

For those interested in management or entrepreneurship, business schools online offer specialized programs in business administration and technology management, blending technical and strategic skills.

Affordable options are available for students seeking to earn their bachelor's degree entirely online. A cheapest online college bachelor degree can help you minimize debt while gaining essential knowledge in computing or related areas.

Engineering is also a popular pathway for tech-focused students. Completing the cheapest online engineering degree can prepare you for high-demand roles in software, electronics, or data systems.

These options offer the flexibility to build your skills at your own pace and often at a lower cost, paving the way for diverse and rewarding careers in technology.

Best Scientists Citing Xing Chen

Trending Scientists

Recently Published Articles