World's Best Scientists 2026 revealed!
Xuegong Zhang

Xuegong Zhang

D-Index & Metrics

Biology and Biochemistry

D-Index
57
Citations
20591
World Ranking
13540
National Ranking
414

Xuegong Zhang publication distribution in Biology and Biochemistry in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Biology and Biochemistry in 2026. The highlighted bar marks where Xuegong Zhang sits on this spectrum.

47–56 publications: 8 scientists 57–66 publications: 35 scientists 67–76 publications: 106 scientists 77–86 publications: 231 scientists 87–96 publications: 414 scientists 97–106 publications: 546 scientists 107–116 publications: 704 scientists 117–126 publications: 849 scientists 127–136 publications: 980 scientists 137–146 publications: 942 scientists 147–156 publications: 969 scientists 157–166 publications: 950 scientists 167–176 publications: 951 scientists 177–186 publications: 915 scientists 187–196 publications: 787 scientists 197–206 publications: 841 scientists 207–216 publications: 735 scientists 217–226 publications: 709 scientists 227–236 publications: 651 scientists 237–246 publications: 605 scientists 247–256 publications: 510 scientists 257–266 publications: 524 scientists 267–276 publications: 434 scientists 277–286 publications: 418 scientists 287–296 publications: 350 scientists 297–306 publications: 363 scientists 307–316 publications: 315 scientists 317–326 publications: 296 scientists 327–336 publications: 261 scientists 337–346 publications: 240 scientists 347–356 publications: 219 scientists 357–366 publications: 197 scientists 367–376 publications: 154 scientists 377–386 publications: 161 scientists 387–396 publications: 155 scientists 397–406 publications: 145 scientists 407–416 publications: 124 scientists 417–426 publications: 112 scientists 427–436 publications: 132 scientists 437–446 publications: 116 scientists 447–456 publications: 99 scientists 457–466 publications: 81 scientists 467–476 publications: 91 scientists 477–486 publications: 80 scientists 487–496 publications: 80 scientists 497–506 publications: 60 scientists 507–516 publications: 36 scientists 517–526 publications: 46 scientists 527–536 publications: 54 scientists 537–546 publications: 44 scientists 547–556 publications: 43 scientists 557–566 publications: 43 scientists 567–576 publications: 42 scientists 577–586 publications: 25 scientists 587–596 publications: 34 scientists 597–606 publications: 23 scientists 607–616 publications: 33 scientists 617–626 publications: 31 scientists 627–636 publications: 27 scientists 637–646 publications: 25 scientists 647–656 publications: 28 scientists 657–666 publications: 34 scientists 667–676 publications: 18 scientists 677–686 publications: 16 scientists 687–696 publications: 10 scientists 697–706 publications: 12 scientists 707–716 publications: 21 scientists 717–726 publications: 12 scientists 727–736 publications: 12 scientists 737–746 publications: 10 scientists 747–756 publications: 7 scientists 757–766 publications: 13 scientists 767–776 publications: 15 scientists 777–786 publications: 13 scientists 787–796 publications: 9 scientists 797–806 publications: 9 scientists 807–816 publications: 7 scientists 817–826 publications: 4 scientists 827–836 publications: 9 scientists 837–846 publications: 7 scientists 847–856 publications: 3 scientists 857–866 publications: 5 scientists 867–876 publications: 5 scientists 877–886 publications: 11 scientists 887–896 publications: 3 scientists 897–906 publications: 4 scientists 907–916 publications: 7 scientists 917–926 publications: 5 scientists 927–936 publications: 6 scientists 937–946 publications: 6 scientists 947–956 publications: 3 scientists 957–966 publications: 7 scientists 967–976 publications: 2 scientists 977–986 publications: 2 scientists 987–996 publications: 1 scientists 997–1,006 publications: 5 scientists 1,007–1,016 publications: 2 scientists 1,017–1,026 publications: 2 scientists 1,027 publications: 1 scientists 1,028+ publications: 100 scientists
47 publications 1,028+

This scientist: 224 publications — 59th percentile

59% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,028 publications or more.

Xuegong Zhang D-index placement in Biology and Biochemistry in 2026

The chart shows the D-index (discipline H-index) distribution of Biology and Biochemistry scientists ranked by Research.com in 2026. The highlighted bar marks where Xuegong Zhang sits on this spectrum.

40–41 D-Index: 80 scientists 42–43 D-Index: 183 scientists 44–45 D-Index: 317 scientists 46–47 D-Index: 504 scientists 48–49 D-Index: 718 scientists 50–51 D-Index: 900 scientists 52–53 D-Index: 1,026 scientists 54–55 D-Index: 1,150 scientists 56–57 D-Index: 1,236 scientists 58–59 D-Index: 1,253 scientists 60–61 D-Index: 1,163 scientists 62–63 D-Index: 1,131 scientists 64–65 D-Index: 1,032 scientists 66–67 D-Index: 897 scientists 68–69 D-Index: 814 scientists 70–71 D-Index: 715 scientists 72–73 D-Index: 709 scientists 74–75 D-Index: 596 scientists 76–77 D-Index: 512 scientists 78–79 D-Index: 473 scientists 80–81 D-Index: 412 scientists 82–83 D-Index: 373 scientists 84–85 D-Index: 358 scientists 86–87 D-Index: 285 scientists 88–89 D-Index: 273 scientists 90–91 D-Index: 227 scientists 92–93 D-Index: 208 scientists 94–95 D-Index: 193 scientists 96–97 D-Index: 153 scientists 98–99 D-Index: 157 scientists 100–101 D-Index: 148 scientists 102–103 D-Index: 120 scientists 104–105 D-Index: 113 scientists 106–107 D-Index: 100 scientists 108–109 D-Index: 86 scientists 110–111 D-Index: 67 scientists 112–113 D-Index: 72 scientists 114–115 D-Index: 73 scientists 116–117 D-Index: 64 scientists 118–119 D-Index: 53 scientists 120–121 D-Index: 60 scientists 122–123 D-Index: 54 scientists 124–125 D-Index: 43 scientists 126–127 D-Index: 38 scientists 128–129 D-Index: 49 scientists 130–131 D-Index: 26 scientists 132–133 D-Index: 18 scientists 134–135 D-Index: 23 scientists 136–137 D-Index: 32 scientists 138–139 D-Index: 32 scientists 140–141 D-Index: 27 scientists 142–143 D-Index: 19 scientists 144–145 D-Index: 22 scientists 146–147 D-Index: 12 scientists 148–149 D-Index: 16 scientists 150–151 D-Index: 14 scientists 152–153 D-Index: 10 scientists 154–155 D-Index: 13 scientists 156–157 D-Index: 10 scientists 158–159 D-Index: 7 scientists 160–161 D-Index: 9 scientists 162–163 D-Index: 13 scientists 164–165 D-Index: 4 scientists 166 D-Index: 4 scientists 167+ D-Index: 98 scientists
40 D-Index 167+

This scientist: 57 D-Index — 31st percentile

31% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 167 D-Index or more.

Overview

Xuegong Zhang is affiliated with Tsinghua University in China and specializes in the field of Biochemistry, Genetics and Molecular Biology. Their research primarily focuses on molecular biology with significant contributions to immunology, biophysics, cancer research, and artificial intelligence applied to biological data.

The scientist's work covers key topics including single-cell and spatial transcriptomics, gene regulatory network analysis, cell image analysis techniques, gene expression and cancer classification, immune cells in cancer, bioinformatics and genomic networks, and cancer genomics and diagnostics.

Recent publications by Xuegong Zhang include:

  • Large-scale foundation model on single-cell transcriptomics, 2024, Nature Methods
  • Large Scale Foundation Model on Single-cell Transcriptomics, 2023, bioRxiv (Cold Spring Harbor Laboratory)
  • SOMDE: a scalable method for identifying spatially variable genes with self-organizing map, 2021, Bioinformatics
  • Cell type annotation of single-cell chromatin accessibility data via supervised Bayesian embedding, 2022, Nature Machine Intelligence
  • Multifunctional, breathable MXene-PU mesh electronic skin for wearable intelligent 12-lead ECG monitoring system, 2022, Chemical Engineering Journal

Xuegong Zhang commonly publishes in venues such as bioRxiv (Cold Spring Harbor Laboratory), Bioinformatics, arXiv (Cornell University), Briefings in Bioinformatics, and Quantitative Biology.

Frequent co-authors include:

  • Lei Wei
  • Minsheng Hao
  • Rui Jiang
  • Sijie Chen
  • Jin Gu

Best Publications

  • DEGseq: an R package for identifying differentially expressed genes from RNA-seq data

    Likun Wang;Zhixing Feng;Xi Wang;Xiaowo Wang

  • A survey of best practices for RNA-seq data analysis

    Ana Conesa;Pedro Madrigal;Pedro Madrigal;Sonia Tarazona;David Gomez-Cabrero

  • The Microarray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

    Leming Shi;Gregory Campbell;Wendell D. Jones;Fabien Campagne

  • Meta-analysis of genome-wide association studies identifies common variants associated with blood pressure variation in east Asians

    Norihiro Kato;Fumihiko Takeuchi;Yasuharu Tabara;Tanika N. Kelly

  • Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine

    Chenghai Xue;Chenghai Xue;Fei Li;Tao He;Guo-Ping Liu;Guo-Ping Liu

  • Understanding ZHENG in traditional Chinese medicine in the context of neuro-endocrine-immune network

    S Li;Z Q Zhang;L J Wu;X G Zhang

  • Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data

    Xuegong Zhang;Xin Lu;Qian Shi;Xiu-qin Xu

  • dbSUPER: a database of super-enhancers in mouse and human genome

    Aziz Khan;Xuegong Zhang

  • MicroRNA identification based on sequence and structure alignment

    Xiaowo Wang;Jing Zhang;Fei Li;Jin Gu

  • Predicting features of breast cancer with gene expression patterns.

    Xuesong Lu;Xin Lu;Xin Lu;Zhigang C. Wang;Zhigang C. Wang;J. Dirk Iglehart;J. Dirk Iglehart

  • On ψ-Learning

    Xiaotong Shen;George C Tseng;Xuegong Zhang;Wing Hung Wong

  • Using class-center vectors to build support vector machines

    Xuegong Zhang

  • DEsingle for detecting three types of differential expression in single-cell RNA-seq data.

    Zhun Miao;Ke Deng;Xiaowo Wang;Xuegong Zhang

  • Computational prediction of associations between long non-coding RNAs and proteins

    Qiongshi Lu;Qiongshi Lu;Qiongshi Lu;Sijin Ren;Ming Lu;Yong Zhang

  • Genome-wide Association Analysis of Blood-Pressure Traits in African-Ancestry Individuals Reveals Common Associated Genes in African and Non-African Populations

    Nora Franceschini;Ervin Fox;Zhaogong Zhang;Zhaogong Zhang;Todd L. Edwards

  • Ivermectin inhibits LPS-induced production of inflammatory cytokines and improves LPS-induced survival in mice.

    X. Zhang;Y. Song;X. Ci;N. An

  • Precise temporal regulation of alternative splicing during neural development.

    Sabastien Matthieu Weyn-Vanhentenryck;Huijuan Feng;Huijuan Feng;Dmytro Ustianenko;Rachel Duffié

  • Kernel Nearest-Neighbor Algorithm

    Kai Yu;Liang Ji;Xuegong Zhang

  • Erratum to: A survey of best practices for RNA-seq data analysis

    Ana Conesa;Pedro Madrigal;Pedro Madrigal;Sonia Tarazona;David Gomez-Cabrero

  • CpG island methylation pattern in different human tissues and its correlation with gene expression

    Shicai Fan;Xuegong Zhang

Frequent Co-Authors

Michael Q. Zhang
Michael Q. Zhang The University of Texas at Dallas
Rui Jiang
Rui Jiang Beijing Jiaotong University
Fengzhu Sun
Fengzhu Sun University of Southern California
Wing Hung Wong
Wing Hung Wong Stanford University
Michael S. Waterman
Michael S. Waterman University of Southern California
Jun S. Liu
Jun S. Liu Harvard University
Jing Wang
Jing Wang Tsinghua University
Pak C. Sham
Pak C. Sham University of Hong Kong
Eric E. Schadt
Eric E. Schadt Icahn School of Medicine at Mount Sinai
Tien Yin Wong
Tien Yin Wong Tsinghua University

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