World's Best Scientists 2026 revealed!
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Biology and Biochemistry
China
2023

D-Index & Metrics

Biology and Biochemistry

D-Index
108
Citations
59038
World Ranking
1031
National Ranking
20

Chemistry

D-Index
106
Citations
58994
World Ranking
930
National Ranking
167

Hualiang Jiang publication distribution in Chemistry in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Chemistry in 2026. The highlighted bar marks where Hualiang Jiang sits on this spectrum.

61–80 publications: 66 scientists 81–100 publications: 302 scientists 101–120 publications: 623 scientists 121–140 publications: 918 scientists 141–160 publications: 1,218 scientists 161–180 publications: 1,350 scientists 181–200 publications: 1,344 scientists 201–220 publications: 1,281 scientists 221–240 publications: 1,216 scientists 241–260 publications: 1,100 scientists 261–280 publications: 979 scientists 281–300 publications: 939 scientists 301–320 publications: 764 scientists 321–340 publications: 643 scientists 341–360 publications: 628 scientists 361–380 publications: 522 scientists 381–400 publications: 459 scientists 401–420 publications: 397 scientists 421–440 publications: 327 scientists 441–460 publications: 270 scientists 461–480 publications: 265 scientists 481–500 publications: 252 scientists 501–520 publications: 201 scientists 521–540 publications: 185 scientists 541–560 publications: 148 scientists 561–580 publications: 148 scientists 581–600 publications: 132 scientists 601–620 publications: 114 scientists 621–640 publications: 104 scientists 641–660 publications: 91 scientists 661–680 publications: 92 scientists 681–700 publications: 73 scientists 701–720 publications: 57 scientists 721–740 publications: 54 scientists 741–760 publications: 67 scientists 761–780 publications: 45 scientists 781–800 publications: 46 scientists 801–820 publications: 39 scientists 821–840 publications: 32 scientists 841–860 publications: 36 scientists 861–880 publications: 29 scientists 881–900 publications: 26 scientists 901–920 publications: 24 scientists 921–940 publications: 14 scientists 941–960 publications: 23 scientists 961–980 publications: 28 scientists 981–1,000 publications: 15 scientists 1,001–1,020 publications: 29 scientists 1,021–1,040 publications: 12 scientists 1,041–1,060 publications: 19 scientists 1,061–1,080 publications: 12 scientists 1,081–1,100 publications: 6 scientists 1,101–1,120 publications: 8 scientists 1,121–1,140 publications: 12 scientists 1,141–1,160 publications: 5 scientists 1,161–1,180 publications: 6 scientists 1,181–1,200 publications: 14 scientists 1,201–1,220 publications: 7 scientists 1,221–1,240 publications: 2 scientists 1,241–1,260 publications: 6 scientists 1,261–1,280 publications: 4 scientists 1,281–1,294 publications: 6 scientists 1,295+ publications: 100 scientists
61 publications 1,295+

This scientist: 844 publications — 98th percentile

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

The last bar groups every scientist with 1,295 publications or more.

Hualiang Jiang D-index placement in Chemistry in 2026

The chart shows the D-index (discipline H-index) distribution of Chemistry scientists ranked by Research.com in 2026. The highlighted bar marks where Hualiang Jiang sits on this spectrum.

40–41 D-Index: 289 scientists 42–43 D-Index: 612 scientists 44–45 D-Index: 808 scientists 46–47 D-Index: 776 scientists 48–49 D-Index: 835 scientists 50–51 D-Index: 861 scientists 52–53 D-Index: 872 scientists 54–55 D-Index: 933 scientists 56–57 D-Index: 1,051 scientists 58–59 D-Index: 930 scientists 60–61 D-Index: 882 scientists 62–63 D-Index: 834 scientists 64–65 D-Index: 731 scientists 66–67 D-Index: 775 scientists 68–69 D-Index: 683 scientists 70–71 D-Index: 646 scientists 72–73 D-Index: 561 scientists 74–75 D-Index: 501 scientists 76–77 D-Index: 437 scientists 78–79 D-Index: 388 scientists 80–81 D-Index: 354 scientists 82–83 D-Index: 292 scientists 84–85 D-Index: 275 scientists 86–87 D-Index: 254 scientists 88–89 D-Index: 235 scientists 90–91 D-Index: 185 scientists 92–93 D-Index: 192 scientists 94–95 D-Index: 155 scientists 96–97 D-Index: 163 scientists 98–99 D-Index: 125 scientists 100–101 D-Index: 105 scientists 102–103 D-Index: 105 scientists 104–105 D-Index: 112 scientists 106–107 D-Index: 88 scientists 108–109 D-Index: 68 scientists 110–111 D-Index: 69 scientists 112–113 D-Index: 65 scientists 114–115 D-Index: 79 scientists 116–117 D-Index: 61 scientists 118–119 D-Index: 44 scientists 120–121 D-Index: 37 scientists 122–123 D-Index: 40 scientists 124–125 D-Index: 33 scientists 126–127 D-Index: 26 scientists 128–129 D-Index: 34 scientists 130–131 D-Index: 35 scientists 132–133 D-Index: 25 scientists 134–135 D-Index: 27 scientists 136–137 D-Index: 17 scientists 138–139 D-Index: 16 scientists 140–141 D-Index: 20 scientists 142–143 D-Index: 20 scientists 144–145 D-Index: 15 scientists 146–147 D-Index: 9 scientists 148–149 D-Index: 9 scientists 150–151 D-Index: 16 scientists 152–153 D-Index: 11 scientists 154–155 D-Index: 9 scientists 156–157 D-Index: 3 scientists 158 D-Index: 3 scientists 159+ D-Index: 98 scientists
40 D-Index 159+

This scientist: 106 D-Index — 95th percentile

95% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 159 D-Index or more.

Research.com Recognitions

  • 2023 - Research.com Biology and Biochemistry in China Leader Award

Overview

Hualiang Jiang was affiliated with the Chinese Academy of Sciences in China. Their research primarily focused on the fields of Biochemistry, Genetics and Molecular Biology, as well as Medicine. Within these broad areas, Jiang contributed substantially to Molecular Biology, Infectious Diseases, Computational Theory and Mathematics, Cellular and Molecular Neuroscience, and Immunology.

The scientist's work covered diverse topics, including:

  • Computational Drug Discovery Methods
  • Receptor Mechanisms and Signaling
  • SARS-CoV-2 and COVID-19 Research
  • COVID-19 Clinical Research Studies
  • Protein Degradation and Inhibitors
  • Protein Structure and Dynamics
  • Machine Learning in Materials Science

Jiang was a frequent contributor to several key scientific journals, with multiple publications appearing in:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Journal of Medicinal Chemistry
  • Nature Communications
  • Acta Pharmacologica Sinica
  • Science China Life Sciences

Among recent papers that Jiang was associated with are:

  • Structure of Mpro from SARS-CoV-2 and discovery of its inhibitors, 2020, Nature
  • Structure-based design of antiviral drug candidates targeting the SARS-CoV-2 main protease, 2020, Science
  • Structural basis for inhibition of the RNA-dependent RNA polymerase from SARS-CoV-2 by remdesivir, 2020, Science
  • TransformerCPI: improving compound-protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments, 2020, Bioinformatics
  • Structures of the Omicron spike trimer with ACE2 and an anti-Omicron antibody, 2022, Science

They collaborated frequently with a number of researchers, including:

  • Mingyue Zheng
  • Kaixian Chen
  • H. Eric Xu
  • Yi Jiang
  • Cheng Luo

Their research involved a combination of experimental and computational approaches. Jiang's work contributed to understanding molecular mechanisms relevant to infectious diseases, especially concerning SARS-CoV-2 and COVID-19. This included studies on viral proteins, antiviral drug candidates, and protein interactions informed by machine learning techniques.

Best Publications

  • Structure of Mpro from SARS-CoV-2 and discovery of its inhibitors

    Zhenming Jin;Zhenming Jin;Xiaoyu Du;Yechun Xu;Yongqiang Deng

  • Structure-based design of antiviral drug candidates targeting the SARS-CoV-2 main protease.

    Wenhao Dai;Wenhao Dai;Bing Zhang;Xia Ming Jiang;Haixia Su

  • Structural basis for inhibition of the RNA-dependent RNA polymerase from SARS-CoV-2 by remdesivir.

    Wanchao Yin;Wanchao Yin;Chunyou Mao;Xiaodong Luan;Xiaodong Luan;Dan Dan Shen

  • Predicting protein-protein interactions based only on sequences information.

    Juwen Shen;Jian Zhang;Xiaomin Luo;Weiliang Zhu

  • PharmMapper server: a web server for potential drug target identification using pharmacophore mapping approach

    Xiaofeng Liu;Sisheng Ouyang;Biao Yu;Yabo Liu

  • Pushing the Boundaries of Molecular Representation for Drug Discovery with the Graph Attention Mechanism.

    Zhaoping Xiong;Zhaoping Xiong;Dingyan Wang;Xiaohong Liu;Xiaohong Liu;Feisheng Zhong

  • Sphingosine-1-phosphate is a missing cofactor for the E3 ubiquitin ligase TRAF2

    Sergio E. Alvarez;Kuzhuvelil B. Harikumar;Nitai C. Hait;Jeremy Allegood

  • Structure of the CCR5 Chemokine Receptor–HIV Entry Inhibitor Maraviroc Complex

    Qiuxiang Tan;Ya Zhu;Jian Li;Zhuxi Chen

  • Small-Molecule Targeting of Oncogenic FTO Demethylase in Acute Myeloid Leukemia.

    Yue Huang;Rui Su;Yue Sheng;Lei Dong;Lei Dong

  • Halogen bonding--a novel interaction for rational drug design?

    Yunxiang Lu;Ting Shi;Yong Wang;Huaiyu Yang

  • Crystal structure of rhodopsin bound to arrestin by femtosecond X-ray laser

    Yanyong Kang;X. Edward Zhou;Xiang Gao;Yuanzheng He

  • Molecular Mimicry Regulates ABA Signaling by SnRK2 Kinases and PP2C Phosphatases

    Fen Fen Soon;Fen Fen Soon;Ley Moy Ng;Ley Moy Ng;X. Edward Zhou;Graham M. West

  • Meclofenamic acid selectively inhibits FTO demethylation of m6A over ALKBH5

    Yue Huang;Jingli Yan;Qi Li;Jiafei Li

  • Structural Basis for Molecular Recognition at Serotonin Receptors

    Chong Wang;Yi Jiang;Yi Jiang;Jinming Ma;Jinming Ma;Huixian Wu

  • TarFisDock: a web server for identifying drug targets with docking approach

    Honglin Li;Zhenting Gao;Ling Kang;Hailei Zhang

  • TransformerCPI: improving compound-protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments.

    Lifan Chen;Xiaoqin Tan;Dingyan Wang;Feisheng Zhong

  • Structures of the Omicron Spike trimer with ACE2 and an anti-Omicron antibody

    Unknown

  • Structure of the human P2Y12 receptor in complex with an antithrombotic drug

    Kaihua Zhang;Jin Zhang;Zhan-Guo Gao;Dandan Zhang

  • Development of Cell-Active N6-Methyladenosine RNA Demethylase FTO Inhibitor

    Baoen Chen;Fei Ye;Lu Yu;Guifang Jia

  • Anti-SARS-CoV-2 activities in vitro of Shuanghuanglian preparations and bioactive ingredients.

    Hai xia Su;Sheng Yao;Wen feng Zhao;Min jun Li

  • Chemoprevention by lipoxygenase and leukotriene pathway inhibitors of vinyl carbamate-induced lung tumors in mice.

    Chul Ho Jeong;Ann M. Bode;Angelo Pugliese;Yong Yeon Cho

  • Computational drug discovery

    Si-sheng Ou-Yang;Jun-yan Lu;Xiang-qian Kong;Zhong-jie Liang

Frequent Co-Authors

Kaixian Chen
Kaixian Chen Chinese Academy of Sciences
Hong Liu
Hong Liu Shandong University
Xu Shen
Xu Shen Nanjing University of Chinese Medicine
Cheng Luo
Cheng Luo Chinese Academy of Sciences
Xiaomin Luo
Xiaomin Luo Chinese Academy of Sciences
Weiliang Zhu
Weiliang Zhu Chinese Academy of Sciences
Mingyue Zheng
Mingyue Zheng Chinese Academy of Sciences
Yu Zhou
Yu Zhou Chinese Academy of Sciences
Deju Ye
Deju Ye Nanjing University
Yun Tang
Yun Tang East China University of Science and Technology

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Related Online Degrees & Career Pathways

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