Dingyan Wang

3.4k total citations · 2 hit papers
47 papers, 2.1k citations indexed

About

Dingyan Wang is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Dingyan Wang has authored 47 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 26 papers in Computational Theory and Mathematics and 15 papers in Materials Chemistry. Recurrent topics in Dingyan Wang's work include Computational Drug Discovery Methods (26 papers), Machine Learning in Materials Science (14 papers) and Protein Structure and Dynamics (7 papers). Dingyan Wang is often cited by papers focused on Computational Drug Discovery Methods (26 papers), Machine Learning in Materials Science (14 papers) and Protein Structure and Dynamics (7 papers). Dingyan Wang collaborates with scholars based in China, Canada and United States. Dingyan Wang's co-authors include Mingyue Zheng, Hualiang Jiang, Xiaomin Luo, Kaixian Chen, Feisheng Zhong, Xiaohong Liu, Xutong Li, Zhaoping Xiong, Xiaozhe Wan and Zhaojun Li and has published in prestigious journals such as Science, Journal of Clinical Investigation and Nature Communications.

In The Last Decade

Dingyan Wang

43 papers receiving 2.1k citations

Hit 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.

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

2019 645 citations Zhaoping Xiong, Dingyan Wang et al. Journal of Medicinal Chemistry profile →
TransformerCPI: improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments

2020 325 citations Lifan Chen, Xiaoqin Tan et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dingyan Wang China	22	1.2k	1.2k	761	141	109	47	2.1k
Djork-Arné Clevert Germany	18	1.5k 1.2×	1.1k 1.0×	765 1.0×	197 1.4×	52 0.5×	38	2.4k
Yinhai Wang United Kingdom	13	669 0.5×	657 0.6×	651 0.9×	231 1.6×	46 0.4×	30	1.8k
Evan N. Feinberg United States	9	2.0k 1.6×	1.7k 1.4×	1.3k 1.7×	306 2.2×	162 1.5×	17	3.2k
Christian Tyrchan Sweden	23	1.7k 1.4×	1.9k 1.6×	1.3k 1.7×	146 1.0×	100 0.9×	56	2.8k
Xutong Li China	20	1.1k 0.9×	1.2k 1.0×	715 0.9×	160 1.1×	165 1.5×	67	2.0k
Nadine Schneider Germany	21	741 0.6×	622 0.5×	487 0.6×	121 0.9×	92 0.8×	41	1.8k
John W. Davies Switzerland	30	1.9k 1.6×	2.0k 1.7×	324 0.4×	51 0.4×	182 1.7×	41	3.3k
Xiaozhe Wan China	10	575 0.5×	681 0.6×	458 0.6×	89 0.6×	234 2.1×	14	1.2k
Shuai Lü China	31	1.2k 1.0×	276 0.2×	426 0.6×	45 0.3×	290 2.7×	144	2.9k
Qing Yuan China	27	889 0.7×	270 0.2×	841 1.1×	25 0.2×	204 1.9×	106	2.3k

Countries citing papers authored by Dingyan Wang

Since Specialization

Citations

This map shows the geographic impact of Dingyan Wang'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 Dingyan Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dingyan Wang more than expected).

Fields of papers citing papers by Dingyan Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dingyan Wang. 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 Dingyan Wang. The network helps show where Dingyan Wang may publish in the future.

Co-authorship network of co-authors of Dingyan Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Dingyan Wang. A scholar is included among the top collaborators of Dingyan Wang 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 Dingyan Wang. Dingyan Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Zhong, Feisheng, et al.. (2025). Folding-Based End-To-End Chemical Drug Design with Uncertainty Estimation: Tackling Hallucination in the Post-GPT Era. Journal of Medicinal Chemistry. 68(6). 6804–6814.

Liu, Xueyan, Jinyu Liu, Jian Zhong, et al.. (2025). AI-driven discovery of brain-penetrant Galectin-3 inhibitors for Alzheimer's disease therapy. Pharmacological Research. 218. 107834–107834.

Wu, Wenyong, Renhong Sun, Dingyan Wang, et al.. (2024). Targeted Degradation of SOS1 Exhibits Potent Anticancer Activity and Overcomes Resistance in KRAS-Mutant Tumors and BCR–ABL–Positive Leukemia. Cancer Research. 85(1). 101–117. 4 indexed citations

He, Xinheng, Lifen Zhao, Yinping Tian, et al.. (2024). Highly accurate carbohydrate-binding site prediction with DeepGlycanSite. Nature Communications. 15(1). 5163–5163. 19 indexed citations

Yu, Jie, Xiang Zhang, Yijie Chen, et al.. (2024). Reducing overconfident errors in molecular property classification using Posterior Network. Patterns. 5(6). 100991–100991. 4 indexed citations

Ren, Qun, Ning Qu, Jingyi Zhou, et al.. (2023). KinomeMETA: meta-learning enhanced kinome-wide polypharmacology profiling. Briefings in Bioinformatics. 25(1). 9 indexed citations

Chen, Lin, Zehong Zhang, Zhenghao Li, et al.. (2023). Learning protein fitness landscapes with deep mutational scanning data from multiple sources. Cell Systems. 14(8). 706–721.e5. 24 indexed citations

Wang, Yitian, Jiacheng Xiong, Xiao Fu, et al.. (2023). LogD7.4 prediction enhanced by transferring knowledge from chromatographic retention time, microscopic pKa and logP. Journal of Cheminformatics. 15(1). 76–76. 19 indexed citations

Wang, Gang, Rui Li, Qun Ren, et al.. (2023). Tora3D: an autoregressive torsion angle prediction model for molecular 3D conformation generation. Journal of Cheminformatics. 15(1). 57–57. 3 indexed citations

10.

Tong, Xiaochu, Dingyan Wang, Xiaoyu Ding, et al.. (2022). Blood–brain barrier penetration prediction enhanced by uncertainty estimation. Journal of Cheminformatics. 14(1). 44–44. 29 indexed citations

11.

Yu, Jie, Dingyan Wang, & Mingyue Zheng. (2022). Uncertainty quantification: Can we trust artificial intelligence in drug discovery?. iScience. 25(8). 104814–104814. 27 indexed citations

12.

Zhang, Zehong, Lifan Chen, Feisheng Zhong, et al.. (2022). Graph neural network approaches for drug-target interactions. Current Opinion in Structural Biology. 73. 102327–102327. 107 indexed citations

13.

Liu, Ming, Jinyi Zhang, Benjamin D. Pinder, et al.. (2021). WAVE2 suppresses mTOR activation to maintain T cell homeostasis and prevent autoimmunity. Science. 371(6536). 33 indexed citations

14.

Wang, Dingyan, Jie Yu, Lifan Chen, et al.. (2021). A hybrid framework for improving uncertainty quantification in deep learning-based QSAR regression modeling. Journal of Cheminformatics. 13(1). 69–69. 20 indexed citations

15.

Xiong, Zhaoping, Ziqiang Cheng, Chi Xu, et al.. (2021). Facing small and biased data dilemma in drug discovery with enhanced federated learning approaches. Science China Life Sciences. 65(3). 529–539. 28 indexed citations

16.

Kwan, Jamie J., Sladjana Slavkovic, Dingyan Wang, et al.. (2020). HACS1 signaling adaptor protein recognizes a motif in the paired immunoglobulin receptor B cytoplasmic domain. Communications Biology. 3(1). 672–672. 4 indexed citations

17.

Wang, Dingyan, Chen Cui, Xiaoyu Ding, et al.. (2019). Improving the Virtual Screening Ability of Target-Specific Scoring Functions Using Deep Learning Methods. Frontiers in Pharmacology. 10. 924–924. 35 indexed citations

18.

Amend, Sarah R., William C. Wilson, Liang Chu, et al.. (2015). Whole Genome Sequence of Multiple Myeloma-Prone C57BL/KaLwRij Mouse Strain Suggests the Origin of Disease Involves Multiple Cell Types. PLoS ONE. 10(5). e0127828–e0127828. 25 indexed citations

19.

Isserlin, Ruth, Daniele Merico, Dingyan Wang, et al.. (2014). Systems analysis reveals down-regulation of a network of pro-survival miRNAs drives the apoptotic response in dilated cardiomyopathy. Molecular BioSystems. 11(1). 239–251. 21 indexed citations

20.

Chiang, Yuting, Weijuan Shao, Dingyan Wang, et al.. (2010). Insulin treatment and high-fat diet feeding reduces the expression of three Tcf genes in rodent pancreas. Journal of Endocrinology. 207(1). 77–86. 19 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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