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Xiaojun Yao

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Chemistry 69 6185 5611 1110 1097 432 17175

Xiaojun Yao publications per year

The chart shows the history of publications by Xiaojun Yao between 2000 and 2026, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Xiaojun Yao published across 27 years, from 2000 to 2026, averaging 20.6 papers a year. Output peaked at 36 publications in 2021. 35 of the 557 publications appeared in the last two years.

No. of publications
10 20 30
Bar chart. Horizontal axis: year, 2000 to 2026. Vertical axis: number of publications, 0 to 36. Peak 36 publications in 2021. 2000: 2 publications 2001: 2 publications 2002: 6 publications 2003: 5 publications 2004: 9 publications 2005: 9 publications 2006: 9 publications 2007: 24 publications 2008: 24 publications 2009: 26 publications 2010: 20 publications 2011: 24 publications 2012: 32 publications 2013: 19 publications 2014: 33 publications 2015: 28 publications 2016: 30 publications 2017: 27 publications 2018: 23 publications 2019: 28 publications 2020: 22 publications 2021: 36 publications 2022: 20 publications 2023: 32 publications 2024: 32 publications 2025: 32 publications 2026: 3 publications
2000 2026

557 publications in total across all disciplines

View publications per year as a table
Xiaojun Yao: publications per year, 2000 to 2026
Year Publications
2000 2
2001 2
2002 6
2003 5
2004 9
2005 9
2006 9
2007 24
2008 24
2009 26
2010 20
2011 24
2012 32
2013 19
2014 33
2015 28
2016 30
2017 27
2018 23
2019 28
2020 22
2021 36
2022 20
2023 32
2024 32
2025 32
2026 3
Total 557
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Xiaojun Yao 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 Xiaojun Yao 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, 421–440 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: 432 publications — 83rd percentile

83% 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
281–300 939
301–320 764
321–340 643
341–360 628
361–380 522
381–400 459
401–420 397
421–440 327 432
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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Xiaojun Yao 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 Xiaojun Yao 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, 68–69 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: 69 D-Index — 66th percentile

66% 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
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 69
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

Xiaojun Yao is affiliated with Macau University of Science and Technology in China and focuses research on biochemistry, genetics, and molecular biology as well as engineering. The scientist's work spans multiple subfields including molecular biology, electrical and electronic engineering, materials chemistry, computational theory and mathematics, and civil and structural engineering.

The primary research topics covered by Xiaojun Yao include computational drug discovery methods, protein structure and dynamics, machine learning applications in materials science, supercapacitor materials and fabrication, conducting polymers and applications, advanced battery technologies research, and perovskite materials and applications.

Frequent publication venues for Yao's research comprise:

  • ACS Chemical Neuroscience
  • SSRN Electronic Journal
  • Journal of Power Sources
  • Briefings in Bioinformatics
  • Physical Chemistry Chemical Physics

Among recent publications are:

  • MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm, 2020, Briefings in Bioinformatics
  • Nrf2: a dark horse in Alzheimer's disease treatment, 2020, Ageing Research Reviews
  • Comprehensive Evaluation of Fourteen Docking Programs on Protein-Peptide Complexes, 2020, Journal of Chemical Theory and Computation
  • Application advances of deep learning methods for de novo drug design and molecular dynamics simulation, 2021, Wiley Interdisciplinary Reviews Computational Molecular Science
  • An effective self-supervised framework for learning expressive molecular global representations to drug discovery, 2021, Briefings in Bioinformatics

Yao has collaborated frequently with a selected group of co-authors, notably:

  • Huanxiang Liu
  • Chunyang Jia
  • Mengxuan Sun
  • Shuoyan Tan
  • Jianxing Xia

The research contributions of Xiaojun Yao bridge several disciplines, emphasizing the integration of computational methods and experimental approaches within molecular biology and engineering contexts. The scientist's work has been disseminated largely through peer-reviewed journals specializing in bioinformatics, chemical neuroscience, and materials science, indicating a multidisciplinary scope with practical implications in drug design, molecular modeling, and advanced material technologies.

Best Publications

  • Molecular dynamics simulations and novel drug discovery.

    Xuewei Liu;Danfeng Shi;Shuangyan Zhou;Hongli Liu

  • Probing the Binding of Scutellarin to Human Serum Albumin by Circular Dichroism, Fluorescence Spectroscopy, FTIR, and Molecular Modeling Method

    Jianniao Tian;Jiaqin Liu;Wenying He;Zhide Hu

  • Comparative study of QSAR/QSPR correlations using support vector machines, radial basis function neural networks, and multiple linear regression.

    Xiaojun Yao;Annick Panaye;Jean-Pierre Doucet;Ruisheng Zhang

  • What Contributes to Serotonin-Norepinephrine Reuptake Inhibitors' Dual-Targeting Mechanism? The Key Role of Transmembrane Domain 6 in Human Serotonin and Norepinephrine Transporters Revealed by Molecular Dynamics Simulation.

    Weiwei Xue;Weiwei Xue;Fengyuan Yang;Fengyuan Yang;Panpan Wang;Panpan Wang;Guoxun Zheng;Guoxun Zheng

  • A retrievable and highly selective fluorescent probe for monitoring sulfide and imaging in living cells.

    Fengping Hou;Liang Huang;Pinxian Xi;Ju Cheng

  • 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

  • Tröger’s base-functionalised organic nanoporous polymer for heterogeneous catalysis

    Xin Du;Yalei Sun;Bien Tan;Qingfeng Teng

  • Nrf2: a dark horse in Alzheimer's disease treatment.

    Alsiddig Osama;Junmin Zhang;Juan Yao;Xiaojun Yao;Xiaojun Yao

  • Near-Infrared and Naked-Eye Fluorescence Probe for Direct and Highly Selective Detection of Cysteine and Its Application in Living Cells

    Unknown

  • Naked-Eye and Near-Infrared Fluorescence Probe for Hydrazine and Its Applications in In Vitro and In Vivo Bioimaging

    Unknown

  • 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

  • A selective, cell-permeable fluorescent probe for Al3+ in living cells.

    Lina Wang;Wenwu Qin;Xiaoliang Tang;Wei Dou

  • 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

  • A study of the binding of C.I. Direct Yellow 9 to human serum albumin using optical spectroscopy and molecular modeling

    Yuanyuan Yue;Xingguo Chen;Jin Qin;Xiaojun Yao

  • Computational identification of the binding mechanism of a triple reuptake inhibitor amitifadine for the treatment of major depressive disorder.

    Weiwei Xue;Weiwei Xue;Panpan Wang;Panpan Wang;Gao Tu;Gao Tu;Fengyuan Yang;Fengyuan Yang

  • Application of a CC Bond‐Forming Conjugate Addition Reaction in Asymmetric Dearomatization of β‐Naphthols

    Dongxu Yang;Linqing Wang;Ming Kai;Dan Li

  • Interaction of erucic acid with bovine serum albumin using a multi-spectroscopic method and molecular docking technique.

    Yang Shu;Weiwei Xue;Xiaoying Xu;Zhimin Jia

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

    Qifeng Bai;Shuo Liu;Yanan Tian;Tingyang Xu

  • Spectroscopic investigation on the binding of antineoplastic drug oxaliplatin to human serum albumin and molecular modeling.

    Yuanyuan Yue;Xingguo Chen;Jin Qin;Xiaojun Yao

  • A retrievable and highly selective fluorescent sensor for detecting copper and sulfide

    Cunji Gao;Xiao Liu;Xiaojie Jin;Jiang Wu

  • Molecular modeling and spectroscopic studies on the binding of guaiacol to human immunoglobulin

    Wenying He;Ying Li;Hongzong Si;Yuming Dong

  • 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

Frequent Co-Authors

Huanxiang Liu
Huanxiang Liu Lanzhou University
Zhide Hu
Zhide Hu Lanzhou University
Feng Zhu
Feng Zhu Zhejiang University
Yu Zong Chen
Yu Zong Chen National University of Singapore
Jianguo Fang
Jianguo Fang Lanzhou University
Weisheng Liu
Weisheng Liu Lanzhou University
Xingguo Chen
Xingguo Chen Lanzhou University
Junzhou Huang
Junzhou Huang The University of Texas at Arlington
Yu Tang
Yu Tang Lanzhou University
Liang Huang
Liang Huang Huazhong University of Science and Technology

External Links

Personal website of Xiaojun Yao

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Best Scientists Citing Xiaojun Yao

Feng Zhu

Feng Zhu

Zhejiang University

Publications: 53

Tingjun Hou

Tingjun Hou

Zhejiang University

Publications: 51

Amir H. Mohammadi

Amir H. Mohammadi

University of KwaZulu-Natal

Publications: 37

Huanxiang Liu

Huanxiang Liu

Lanzhou University

Publications: 32

Ali Akbar Saboury

Ali Akbar Saboury

University of Tehran

Publications: 30

Zhide Hu

Zhide Hu

Lanzhou University

Publications: 29

Youyong Li

Youyong Li

Soochow University

Publications: 24

John Z. H. Zhang

John Z. H. Zhang

New York University

Publications: 21

Dong-Sheng Cao

Dong-Sheng Cao

Central South University

Publications: 21

Farhad Gharagheizi

Farhad Gharagheizi

Georgia Institute of Technology

Publications: 20

Igor V. Tetko

Igor V. Tetko

Helmholtz Zentrum München

Publications: 20

Mohammad Reza Ganjali

Mohammad Reza Ganjali

University of Tehran

Publications: 18

Yi Liu

Yi Liu

Wuhan University

Publications: 18

Quan Zou

Quan Zou

University of Electronic Science and Technology of China

Publications: 18

Jerzy Leszczynski

Jerzy Leszczynski

Jackson State University

Publications: 16

Cheal Kim

Cheal Kim

Seoul National University of Science and Technology

Publications: 16

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