World's Best Scientists 2026 revealed!
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Huanxiang Liu

Huanxiang Liu

Lanzhou University
China

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Chemistry 48 15146 13649 2349 2330 273 9434

Huanxiang Liu publications per year

The chart shows the history of publications by Huanxiang Liu between 1990 and 2026, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Huanxiang Liu published across 37 years, from 1990 to 2026, averaging 9.3 papers a year. Output peaked at 33 publications in 2025. 35 of the 344 publications appeared in the last two years.

No. of publications
10 20 30
Bar chart. Horizontal axis: year, 1990 to 2026. Vertical axis: number of publications, 0 to 33. Peak 33 publications in 2025. 1990: 1 publication 1991: 0 publications 1992: 0 publications 1993: 0 publications 1994: 0 publications 1995: 0 publications 1996: 0 publications 1997: 0 publications 1998: 0 publications 1999: 0 publications 2000: 0 publications 2001: 0 publications 2002: 0 publications 2003: 3 publications 2004: 9 publications 2005: 10 publications 2006: 7 publications 2007: 17 publications 2008: 5 publications 2009: 12 publications 2010: 12 publications 2011: 9 publications 2012: 14 publications 2013: 8 publications 2014: 19 publications 2015: 16 publications 2016: 16 publications 2017: 11 publications 2018: 13 publications 2019: 18 publications 2020: 11 publications 2021: 20 publications 2022: 19 publications 2023: 27 publications 2024: 32 publications 2025: 33 publications 2026: 2 publications
1990 2026

344 publications in total across all disciplines

View publications per year as a table
Huanxiang Liu: publications per year, 1990 to 2026
Year Publications
1990 1
1991 0
1992 0
1993 0
1994 0
1995 0
1996 0
1997 0
1998 0
1999 0
2000 0
2001 0
2002 0
2003 3
2004 9
2005 10
2006 7
2007 17
2008 5
2009 12
2010 12
2011 9
2012 14
2013 8
2014 19
2015 16
2016 16
2017 11
2018 13
2019 18
2020 11
2021 20
2022 19
2023 27
2024 32
2025 33
2026 2
Total 344
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Huanxiang Liu 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 Huanxiang Liu sits on this spectrum.

No. of scientists
250 500 750 1,000 1,250
Bar chart with 63 bars. Horizontal axis: publications, 61–80 to 1,295+. Vertical axis: number of scientists, 0 to 1,350. Most scientists, 1,350, have 161–180 publications. The last bar groups every scientist with 1,295 publications or more. The highlighted bar, 261–280 publications, is where this scientist sits. 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
61–80 publications 1,295+

This scientist: 273 publications — 56th percentile

56% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Chemistry scientists by publication count, Research.com 2026 ranking edition. Based on 17,934 ranked scientists.
Publications Scientists This scientist
61–80 66
81–100 302
101–120 623
121–140 918
141–160 1,218
161–180 1,350
181–200 1,344
201–220 1,281
221–240 1,216
241–260 1,100
261–280 979 273
281–300 939
301–320 764
321–340 643
341–360 628
361–380 522
381–400 459
401–420 397
421–440 327
441–460 270
461–480 265
481–500 252
501–520 201
521–540 185
541–560 148
561–580 148
581–600 132
601–620 114
621–640 104
641–660 91
661–680 92
681–700 73
701–720 57
721–740 54
741–760 67
761–780 45
781–800 46
801–820 39
821–840 32
841–860 36
861–880 29
881–900 26
901–920 24
921–940 14
941–960 23
961–980 28
981–1,000 15
1,001–1,020 29
1,021–1,040 12
1,041–1,060 19
1,061–1,080 12
1,081–1,100 6
1,101–1,120 8
1,121–1,140 12
1,141–1,160 5
1,161–1,180 6
1,181–1,200 14
1,201–1,220 7
1,221–1,240 2
1,241–1,260 6
1,261–1,280 4
1,281–1,294 6
1,295+ 100
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Huanxiang Liu 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 Huanxiang Liu sits on this spectrum.

No. of scientists
250 500 750 1,000
Bar chart with 61 bars. Horizontal axis: D-Index, 40–41 to 159+. Vertical axis: number of scientists, 0 to 1,051. Most scientists, 1,051, have 56–57 D-Index. The last bar groups every scientist with 159 D-Index or more. The highlighted bar, 48–49 D-Index, is where this scientist sits. 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
40–41 D-Index 159+

This scientist: 48 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

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

View D-Index distribution as a table
Number of Chemistry scientists by D-index, Research.com 2026 ranking edition. Based on 17,934 ranked scientists.
D-Index Scientists This scientist
40–41 289
42–43 612
44–45 808
46–47 776
48–49 835 48
50–51 861
52–53 872
54–55 933
56–57 1,051
58–59 930
60–61 882
62–63 834
64–65 731
66–67 775
68–69 683
70–71 646
72–73 561
74–75 501
76–77 437
78–79 388
80–81 354
82–83 292
84–85 275
86–87 254
88–89 235
90–91 185
92–93 192
94–95 155
96–97 163
98–99 125
100–101 105
102–103 105
104–105 112
106–107 88
108–109 68
110–111 69
112–113 65
114–115 79
116–117 61
118–119 44
120–121 37
122–123 40
124–125 33
126–127 26
128–129 34
130–131 35
132–133 25
134–135 27
136–137 17
138–139 16
140–141 20
142–143 20
144–145 15
146–147 9
148–149 9
150–151 16
152–153 11
154–155 9
156–157 3
158 3
159+ 98
Download as CSV

Overview

Huanxiang Liu is affiliated with Lanzhou University in China and has contributed extensively to the fields of biochemistry, genetics, and molecular biology with a particular focus on molecular biology and computational approaches.

Their research encompasses several main topics, including:

  • Computational Drug Discovery Methods
  • Protein Structure and Dynamics
  • Machine Learning in Materials Science
  • Cancer Therapeutics and Mechanisms
  • Machine Learning in Bioinformatics
  • RNA and Protein Synthesis Mechanisms
  • Receptor Mechanisms and Signaling

Liu has published in numerous scientific venues, with frequent appearances in:

  • Journal of Chemical Information and Modeling
  • ACS Chemical Neuroscience
  • International Journal of Molecular Sciences
  • Briefings in Bioinformatics
  • Wiley Interdisciplinary Reviews Computational Molecular Science

Selected recent papers include:

  • "MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm," 2020, Briefings in Bioinformatics
  • "CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity," 2020, Environmental Health Perspectives
  • "Ligand recognition and allosteric regulation of DRD1-Gs signaling complexes," 2021, Cell
  • "Application advances of deep learning methods for de novo drug design and molecular dynamics simulation," 2021, Wiley Interdisciplinary Reviews Computational Molecular Science
  • "RetroPrime: A Diverse, plausible and Transformer-based method for Single-Step retrosynthesis predictions," 2021, Chemical Engineering Journal

Frequent co-authors in Liu's body of work include:

  • Xiaojun Yao
  • Qianqian Zhang
  • Tingjun Hou
  • Shuoyan Tan
  • Henry H. Y. Tong

Their scholarship bridges computational theory and mathematics with applied molecular sciences, reflecting an interdisciplinary approach. The combination of molecular biology, machine learning, and materials chemistry is evident in their research output.

Overall, the scientific contributions cover fundamental and computational drug discovery methods, detailed studies on protein structure and dynamics, and the integration of machine learning techniques into molecular simulation and retrosynthesis prediction models. This body of work intersects medicine and biochemistry, aiming to advance understanding in molecular mechanisms and therapeutic strategies.

Best Publications

  • Molecular dynamics simulations and novel drug discovery.

    Xuewei Liu;Danfeng Shi;Shuangyan Zhou;Hongli Liu

  • Applicability domains for classification problems: Benchmarking of distance to models for Ames mutagenicity set.

    Iurii Sushko;Sergii Novotarskyi;Robert Körner;Anil Kumar Pandey

  • MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm.

    Qifeng Bai;Shuoyan Tan;Tingyang Xu;Huanxiang Liu

  • CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity.

    Kamel Mansouri;Nicole Kleinstreuer;Ahmed M. Abdelaziz;Domenico Alberga

  • Accurate quantitative structure-property relationship model to predict the solubility of C60 in various solvents based on a novel approach using a least-squares support vector machine.

    Huanxiang Liu;Xiaojun Yao;Ruisheng Zhang;Mancang Liu

  • Molecular modeling study of checkpoint kinase 1 inhibitors by multiple docking strategies and prime/MM–GBSA calculation

    Juan Du;Huijun Sun;Lili Xi;Jiazhong Li

  • Diagnosing breast cancer based on support vector machines.

    Huanxiang Liu;Ruisheng Zhang;Feng Luan;Xiaojun Yao

  • Prediction of the isoelectric point of an amino acid based on GA-PLS and SVMs.

    Huanxiang Liu;Ruisheng Zhang;Xiaojun Yao;Mancang Liu

  • The molecular mechanism of bisphenol A (BPA) as an endocrine disruptor by interacting with nuclear receptors: insights from molecular dynamics (MD) simulations.

    Lanlan Li;Qianqian Wang;Yan Zhang;Yuzhen Niu

  • Ligand recognition and allosteric regulation of DRD1-Gs signaling complexes

    Peng Xiao;Wei Yan;Lu Gou;Ya Ni Zhong

  • Application advances of deep learning methods for de novo drug design and molecular dynamics simulation

    Qifeng Bai;Shuo Liu;Yanan Tian;Tingyang Xu

  • QSAR Prediction of Estrogen Activity for a Large Set of Diverse Chemicals under the Guidance of OECD Principles

    Unknown

  • RetroPrime: A Diverse, plausible and Transformer-based method for Single-Step retrosynthesis predictions

    Xiaorui Wang;Yuquan Li;Jiezhong Qiu;Guangyong Chen

  • QSAR models for the prediction of binding affinities to human serum albumin using the heuristic method and a support vector machine.

    C. X. Xue;Ruisheng Zhang;Huanxiang Liu;Xiaojun Yao

  • Molecular Dynamics Simulation, Free Energy Calculation and Structure-Based 3D-QSAR Studies of B-RAF Kinase Inhibitors

    Ying Yang;Jin Qin;Huanxiang Liu;Xiaojun Yao

  • Molecular modeling study on the resistance mechanism of HCV NS3/4A serine protease mutants R155K, A156V and D168A to TMC435

    Weiwei Xue;Dabo Pan;Ying Yang;Huanxiang Liu

  • Influence of Interface Structure on the Properties of ZnO/Graphene Composites: A Theoretical Study by Density Functional Theory Calculations

    Wei Geng;Xuefei Zhao;Huanxiang Liu;Xiaojun Yao

  • Preparation and In vitro Evaluation of Ethosomal Total Alkaloids of Sophora alopecuroides Loaded by a Transmembrane pH-Gradient Method

    Yan Zhou;Yuhui Wei;Huanxiang Liu;Guoqiang Zhang

  • QSAR study of ethyl 2-[(3-methyl-2,5-dioxo(3-pyrrolinyl))amino]-4-(trifluoromethyl) pyrimidine-5-carboxylate: an inhibitor of AP-1 and NF-kappa B mediated gene expression based on support vector machines.

    Huanxiang Liu;Ruisheng Zhang;Xiaojun Yao;Mancang Liu

  • Molecular basis of the interaction for an essential subunit PA-PB1 in influenza virus RNA polymerase: insights from molecular dynamics simulation and free energy calculation.

    Huanxiang Liu;Xiaojun Yao

  • Enhanced photocatalytic properties of titania–graphene nanocomposites: a density functional theory study

    Wei Geng;Huanxiang Liu;Xiaojun Yao

  • Molecular dynamics simulation and free energy calculation studies of the binding mechanism of allosteric inhibitors with p38α MAP kinase.

    Ying Yang;Yulin Shen;Huanxiang Liu;Xiaojun Yao

  • Spectroscopic studies on binding of shikonin to human serum albumin

    Wenying He;Ying Li;Jianniao Tian;Huanxiang Liu

Frequent Co-Authors

Xiaojun Yao
Xiaojun Yao Macau University of Science and Technology
Zhide Hu
Zhide Hu Lanzhou University
Junzhou Huang
Junzhou Huang The University of Texas at Arlington
Roberto Todeschini
Roberto Todeschini University of Milano-Bicocca
Kuo Hsiung Lee
Kuo Hsiung Lee University of Minnesota
Eugene N. Muratov
Eugene N. Muratov University of North Carolina at Chapel Hill
Denis Fourches
Denis Fourches North Carolina State University
Igor V. Tetko
Igor V. Tetko Helmholtz Zentrum München
Dragos Horvath
Dragos Horvath University of Strasbourg
Karl-Werner Schramm
Karl-Werner Schramm Technical University of Munich

External Links

Personal website of Huanxiang Liu

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