World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
6725
World Ranking
8056
National Ranking
1057

Lin Gao 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 Lin Gao 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: 183 publications — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Lin Gao 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 Lin Gao 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: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Overview

Lin Gao is affiliated with Xidian University in China and has an extensive research portfolio primarily in the fields of Biochemistry, Genetics and Molecular Biology, and Medicine. Their work spans several subfields including Molecular Biology, Immunology, Genetics, Endocrine and Autonomic Systems, and Cell Biology.

The scientist's research topics focus significantly on the neuroscience of respiration and sleep, high altitude and hypoxia, and hemoglobin structure and function. Additionally, they have engaged in studies involving single-cell and spatial transcriptomics, immune cells in cancer, phagocytosis and immune regulation, and RNA interference and gene delivery.

Lin Gao has published in numerous reputable venues with multiple contributions in the following journals and platforms:

  • Nature
  • Scientific Reports
  • arXiv (Cornell University)
  • Nature Communications
  • Journal of Translational Medicine

Frequent coauthors associated with Lin Gao include José López-Barneo, Patricia Ortega-Sáenz, Patricia González-Rodríguez, Navdeep S. Chandel, and Alejandro Moreno-Domínguez.

Several notable recent papers highlight Lin Gao's research contributions. These include:

  • "Disruption of mitochondrial complex I induces progressive parkinsonism," 2021, Nature
  • "Mitochondrial integrated stress response controls lung epithelial cell fate," 2023, Nature
  • "Role of Medium-Chain Fatty Acids in Healthy Metabolism: A Clinical Perspective," 2021, Trends in Endocrinology and Metabolism
  • "Acute O 2 sensing through HIF2α-dependent expression of atypical cytochrome oxidase subunits in arterial chemoreceptors," 2020, Science Signaling
  • "Dual mRNA co-delivery for in situ generation of phagocytosis-enhanced CAR macrophages augments hepatocellular carcinoma immunotherapy," 2023, Journal of Controlled Release

Best Publications

  • Remote sensing algorithms for estimation of fractional vegetation cover using pure vegetation index values: A review

    Lin Gao;Xiaofei Wang;Xiaofei Wang;Brian Alan Johnson;Qingjiu Tian

  • VV-Net: Voxel VAE Net With Group Convolutions for Point Cloud Segmentation

    Hsien-Yu Meng;Lin Gao;Yu-Kun Lai;Dinesh Manocha

  • SDM-NET: deep generative network for structured deformable mesh

    Lin Gao;Jie Yang;Tong Wu;Yu-Jie Yuan

  • Long non-coding RNAs function annotation: a global prediction method based on bi-colored networks

    Xingli Guo;Lin Gao;Qi Liao;Hui Xiao

  • Variational Autoencoders for Deforming 3D Mesh Models

    Qingyang Tan;Lin Gao;Yu-Kun Lai;Shihong Xia

  • Semi-supervised clustering algorithm for community structure detection in complex networks

    Xiaoke Ma;Lin Gao;Xuerong Yong;Lidong Fu

  • Comparative pan-cancer DNA methylation analysis reveals cancer common and specific patterns

    Xiaofei Yang;Lin Gao;Shihua Zhang

  • 3D-FUTURE: 3D Furniture shape with TextURE

    Huan Fu;Rongfei Jia;Lin Gao;Mingming Gong

  • Advances in long noncoding RNAs: identification, structure prediction and function annotation.

    Xingli Guo;Lin Gao;Yu Wang;David K. Y. Chiu

  • Identification of overlapping and non-overlapping community structure by fuzzy clustering in complex networks

    Peng Gang Sun;Lin Gao;Shan Shan Han

  • Graph CNNs with Motif and Variable Temporal Block for Skeleton-Based Action Recognition.

    Yu-Hui Wen;Lin Gao;Hongbo Fu;Fang-Lue Zhang

  • DeepFaceDrawing: deep generation of face images from sketches

    Shu-Yu Chen;Wanchao Su;Lin Gao;Shihong Xia

  • CytoTalk: De novo construction of signal transduction networks using single-cell transcriptomic data

    Yuxuan Hu;Tao Peng;Lin Gao;Kai Tan;Kai Tan

  • Inferring drug-disease associations based on known protein complexes

    Liang Yu;Jianbin Huang;Zhixin Ma;Jing Zhang

  • Evaluation and comparison of multi-omics data integration methods for cancer subtyping.

    Ran Duan;Lin Gao;Yong Gao;Yuxuan Hu

  • Automatic unpaired shape deformation transfer

    Lin Gao;Jie Yang;Yi-Ling Qiao;Yu-Kun Lai

  • A survey on deep geometry learning: From a representation perspective

    Yun-Peng Xiao;Yu-Kun Lai;Fang-Lue Zhang;Chunpeng Li

  • An optimization approach for extracting and encoding consistent maps in a shape collection

    Qi-Xing Huang;Guo-Xin Zhang;Lin Gao;Shi-Min Hu

  • Predicting Potential Drugs for Breast Cancer based on miRNA and Tissue Specificity.

    Liang Yu;Jin Zhao;Lin Gao

  • Prediction of human disease-related gene clusters by clustering analysis.

    Peng Gang Sun;Lin Gao;Shan Han

  • Biological network analysis: insights into structure and functions

    Xiaoke Ma;Lin Gao

  • 3D-FRONT: 3D Furnished Rooms with layOuts and semaNTics

    Huan Fu;Bowen Cai;Lin Gao;Lingxiao Zhang

Frequent Co-Authors

Yu-Kun Lai
Yu-Kun Lai Cardiff University
Hongbo Fu
Hongbo Fu City University of Hong Kong
Paul L. Rosin
Paul L. Rosin Cardiff University
Hao Zhang
Hao Zhang Simon Fraser University
Kai Tan
Kai Tan Children's Hospital of Philadelphia
Leif Kobbelt
Leif Kobbelt RWTH Aachen University
Dinesh Manocha
Dinesh Manocha University of Maryland, College Park
Nikola Kasabov
Nikola Kasabov Auckland University of Technology
Xilin Chen
Xilin Chen University of Chinese Academy of Sciences
Leonidas J. Guibas
Leonidas J. Guibas Stanford University

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