Weihua Li

14.7k total citations · 5 hit papers
251 papers, 10.8k citations indexed

About

Weihua Li is a scholar working on Computational Theory and Mathematics, Molecular Biology and Pharmacology. According to data from OpenAlex, Weihua Li has authored 251 papers receiving a total of 10.8k indexed citations (citations by other indexed papers that have themselves been cited), including 145 papers in Computational Theory and Mathematics, 128 papers in Molecular Biology and 59 papers in Pharmacology. Recurrent topics in Weihua Li's work include Computational Drug Discovery Methods (145 papers), Pharmacogenetics and Drug Metabolism (49 papers) and Analytical Chemistry and Chromatography (36 papers). Weihua Li is often cited by papers focused on Computational Drug Discovery Methods (145 papers), Pharmacogenetics and Drug Metabolism (49 papers) and Analytical Chemistry and Chromatography (36 papers). Weihua Li collaborates with scholars based in China, United States and Japan. Weihua Li's co-authors include Yun Tang, Guixia Liu, Feixiong Cheng, Zengrui Wu, Jie Shen, Philip W. Lee, Hongbin Yang, Yadi Zhou, Lixia Sun and Yingchun Cai and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Weihua Li

244 papers receiving 10.6k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

admetSAR: A Comprehensive Source and Free Tool for Assessment of Chemical ADMET Properties

2012 1.7k citations Weihua Li, Zengrui Wu et al. Journal of Chemical Information and Modeling profile →
admetSAR 2.0: web-service for prediction and optimization of chemical ADMET properties

2018 955 citations Hongbin Yang, Chaofeng Lou et al. profile →
Prediction of Drug-Target Interactions and Drug Repositioning via Network-Based Inference

2012 638 citations Weihua Li, Guixia Liu et al. profile →
ADMET-score – a comprehensive scoring function for evaluation of chemical drug-likeness

2018 446 citations Hongbin Yang, Yingchun Cai et al. profile →
admetSAR3.0: a comprehensive platform for exploration, prediction and optimization of chemical ADMET properties

2024 59 citations Chaofeng Lou, Weihua Li et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Weihua Li China	47	5.1k	5.1k	1.6k	1.5k	975	251	10.8k
Yun Tang China	48	5.1k 1.0×	5.2k 1.0×	1.4k 0.9×	2.0k 1.3×	1.1k 1.2×	347	11.3k
Robert Preißner Germany	46	3.3k 0.6×	5.4k 1.1×	1.1k 0.7×	1.3k 0.8×	1.1k 1.1×	214	10.9k
Paul Thiessen United States	24	4.3k 0.8×	6.0k 1.2×	1.1k 0.7×	1.1k 0.8×	1.2k 1.2×	38	12.8k
Siqian He United States	13	4.3k 0.8×	6.1k 1.2×	1.1k 0.7×	939 0.6×	1.2k 1.2×	14	12.4k
Asta Gindulytė United States	19	4.5k 0.9×	5.9k 1.2×	1.1k 0.7×	1.1k 0.7×	1.2k 1.3×	27	12.5k
Tiejun Cheng United States	24	4.1k 0.8×	5.3k 1.0×	916 0.6×	1.0k 0.7×	1.1k 1.1×	42	10.4k
Guixia Liu China	39	4.0k 0.8×	3.4k 0.7×	1.1k 0.7×	1.4k 1.0×	842 0.9×	199	7.8k

Countries citing papers authored by Weihua Li

Since Specialization

Citations

This map shows the geographic impact of Weihua Li's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Weihua Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weihua Li more than expected).

Fields of papers citing papers by Weihua Li

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Weihua Li. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Weihua Li. The network helps show where Weihua Li may publish in the future.

Co-authorship network of co-authors of Weihua Li

This figure shows the co-authorship network connecting the top 25 collaborators of Weihua Li. A scholar is included among the top collaborators of Weihua Li based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Weihua Li. Weihua Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Li, Xiang, et al.. (2025). MMPK: A Multimodal Deep Learning Framework to Predict Human Oral Pharmacokinetic Parameters. Journal of Medicinal Chemistry. 68(15). 16678–16690.

Yu, Hongbo, Guixia Liu, Weihua Li, et al.. (2025). Cocry-pred: A Dynamic Resource Propagation Method for Cocrystal Prediction. Journal of Chemical Information and Modeling. 65(6). 2868–2881.

Huang, Zejun, et al.. (2024). In silico prediction of ocular toxicity of compounds using explainable machine learning and deep learning approaches. Journal of Applied Toxicology. 44(6). 892–907. 3 indexed citations

Huang, Zejun, Hao Duan, Weihua Li, et al.. (2024). In Silico Prediction of ERRα Agonists Based on Combined Features and Stacking Ensemble Method. ChemMedChem. 19(20). e202400298–e202400298.

Liu, Guixia, et al.. (2024). Evaluation of machine learning models for cytochrome P450 3A4, 2D6, and 2C9 inhibition. Journal of Applied Toxicology. 44(7). 1050–1066. 3 indexed citations

Huang, Zejun, et al.. (2024). AttentiveSkin: To Predict Skin Corrosion/Irritation Potentials of Chemicals via Explainable Machine Learning Methods. Chemical Research in Toxicology. 37(2). 361–373. 9 indexed citations

Liu, Guixia, et al.. (2024). Unraveling the Ligand-Binding Sites of CYP3A4 by Molecular Dynamics Simulations with Solvent Probes. Journal of Chemical Information and Modeling. 64(8). 3451–3464. 6 indexed citations

Li, Weihua. (2024). Effects of Shixiao Huoxue Decoction on pain, tumor necrosis factor-α, and interleukin-8 in patients with adenomyosis. American Journal of Translational Research. 16(2). 584–591. 1 indexed citations

Sun, Huimin, Yang Qing, Meng Ding, et al.. (2023). Prediction of IDO1 Inhibitors by a Fingerprint‐Based Stacking Ensemble Model Named IDO1Stack. ChemMedChem. 18(17). e202300151–e202300151. 3 indexed citations

10.

Wu, Zengrui, et al.. (2023). EDC-Predictor: A Novel Strategy for Prediction of Endocrine-Disrupting Chemicals by Integrating Pharmacological and Toxicological Profiles. Environmental Science & Technology. 57(46). 18013–18025. 26 indexed citations

11.

Lou, Chaofeng, Hongbin Yang, Weihua Li, et al.. (2023). Chemical rules for optimization of chemical mutagenicity via matched molecular pairs analysis and machine learning methods. Journal of Cheminformatics. 15(1). 35–35. 8 indexed citations

12.

Zheng, Lulu, Bin Zhu, Zengrui Wu, et al.. (2023). Pharmaceutical Cocrystal Discovery via 3D-SMINBR: A New Network Recommendation Tool Augmented by 3D Molecular Conformations. Journal of Chemical Information and Modeling. 63(14). 4301–4311. 2 indexed citations

13.

Li, Longqiang, Lu Zhou, Guixia Liu, Yun Tang, & Weihua Li. (2023). Machine Learning Models to Predict Cytochrome P450 2B6 Inhibitors and Substrates. Chemical Research in Toxicology. 36(8). 1332–1344. 7 indexed citations

14.

Wang, Xin, et al.. (2022). Study on the mode of action between Apis mellifera (α8)2(β1)3 nAChR and typical neonicotinoids versus flupyradifurone with different bee-toxic levels. Journal of Molecular Graphics and Modelling. 114. 108177–108177. 10 indexed citations

15.

Lou, Chaofeng, Hongbin Yang, Weihua Li, et al.. (2022). IDL-PPBopt: A Strategy for Prediction and Optimization of Human Plasma Protein Binding of Compounds via an Interpretable Deep Learning Method. Journal of Chemical Information and Modeling. 62(11). 2788–2799. 13 indexed citations

16.

Liu, Shao-Chuang, et al.. (2021). Snapshotting the transient conformations and tracing the multiple pathways of single peptide folding using a solid-state nanopore. Chemical Science. 12(9). 3282–3289. 49 indexed citations

17.

Chen, Yue, Junhao Li, Zengrui Wu, et al.. (2020). Computational Insight into the Allosteric Activation Mechanism of Farnesoid X Receptor. Journal of Chemical Information and Modeling. 60(3). 1540–1550. 7 indexed citations

18.

Sun, Lixia, Hongbin Yang, Yingchun Cai, et al.. (2019). In Silico Prediction of Endocrine Disrupting Chemicals Using Single-Label and Multilabel Models. Journal of Chemical Information and Modeling. 59(3). 973–982. 26 indexed citations

19.

Zhang, Xiaoxiang, et al.. (2017). QTL Analysis of Under-ear Internode Length Based on SSSL Population. ACTA AGRONOMICA SINICA. 44(4). 522–532. 2 indexed citations

20.

Jiang, Peihua, Xia Li, Dieter Gläser, et al.. (2012). Major taste loss in carnivorous mammals. Proceedings of the National Academy of Sciences. 109(13). 4956–4961. 191 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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