Chengkun Wu

4.9k total citations · 2 hit papers
74 papers, 3.0k citations indexed

About

Chengkun Wu is a scholar working on Molecular Biology, Artificial Intelligence and Materials Chemistry. According to data from OpenAlex, Chengkun Wu has authored 74 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Molecular Biology, 22 papers in Artificial Intelligence and 19 papers in Materials Chemistry. Recurrent topics in Chengkun Wu's work include Computational Drug Discovery Methods (18 papers), Biomedical Text Mining and Ontologies (13 papers) and Machine Learning in Materials Science (12 papers). Chengkun Wu is often cited by papers focused on Computational Drug Discovery Methods (18 papers), Biomedical Text Mining and Ontologies (13 papers) and Machine Learning in Materials Science (12 papers). Chengkun Wu collaborates with scholars based in China, United Kingdom and Hong Kong. Chengkun Wu's co-authors include Dongsheng Cao, Tingjun Hou, Jiacai Yi, Zhenhua Wu, Xiangxiang Zeng, Zhijiang Yang, Aiping Lü, Chang‐Yu Hsieh, Guo‐Li Xiong and Xiang Chen and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and Advanced Functional Materials.

In The Last Decade

Chengkun Wu

67 papers receiving 3.0k 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.

ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties

2021 1.7k citations Guo‐Li Xiong, Zhenhua Wu et al. Nucleic Acids Research profile →
ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision support

2024 349 citations Li Fu, Shaohua Shi et al. Nucleic Acids Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Chengkun Wu China	18	1.3k	1.0k	559	338	286	74	3.0k
Horacio Pérez‐Sánchez Spain	34	1.8k 1.4×	954 0.9×	595 1.1×	409 1.2×	159 0.6×	219	4.2k
Zhenming Liu China	32	2.1k 1.6×	884 0.8×	644 1.2×	338 1.0×	171 0.6×	198	4.3k
Rengül Çetin-Atalay Türkiye	33	2.0k 1.6×	670 0.6×	779 1.4×	312 0.9×	140 0.5×	140	3.8k
Santiago Vilar Spain	31	2.0k 1.5×	1.8k 1.7×	838 1.5×	214 0.6×	155 0.5×	77	3.9k
S. Joshua Swamidass United States	33	1.9k 1.5×	1.7k 1.7×	248 0.4×	457 1.4×	382 1.3×	87	3.4k
Hua Gao China	27	1.5k 1.2×	1.8k 1.8×	741 1.3×	999 3.0×	126 0.4×	179	4.5k
Daniel Reker United States	25	1.4k 1.1×	1.1k 1.0×	509 0.9×	434 1.3×	92 0.3×	60	2.7k
Alexey Zakharov United States	29	1.0k 0.8×	1.1k 1.1×	400 0.7×	233 0.7×	84 0.3×	117	2.5k
Hong Fang United States	40	2.0k 1.6×	1.6k 1.5×	294 0.5×	205 0.6×	201 0.7×	83	4.8k
Tiago Rodrigues Portugal	30	1.7k 1.4×	1.2k 1.1×	970 1.7×	566 1.7×	100 0.3×	119	3.8k

Countries citing papers authored by Chengkun Wu

Since Specialization

Citations

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

Fields of papers citing papers by Chengkun Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chengkun Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Chengkun Wu. A scholar is included among the top collaborators of Chengkun Wu 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 Chengkun Wu. Chengkun Wu 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

Zhang, Duo, et al.. (2026). LAMBench: a benchmark for large atomistic models. npj Computational Materials. 12(1). 1 indexed citations

Ye, Keng, Kevin Lin, Chengkun Wu, et al.. (2025). Ultrasmall platinum single-atom enzyme alleviates oxidative stress and macrophage polarization induced by acute kidney ischemia–reperfusion injury through inhibition of cell death storm. Journal of Nanobiotechnology. 23(1). 320–320. 6 indexed citations

Chen, Fang, Xi Yang, Ze Wu, et al.. (2025). Melatonin Alleviates Retina Angiogenesis by Targeting Fibronectin and the VEGF Pathway. The FASEB Journal. 39(19). e71073–e71073.

Yi, Jiacai, Dejun Jiang, Chengkun Wu, et al.. (2025). Pushing the boundaries of few-shot learning for low-data drug discovery with a Bayesian meta-learning hypernetwork framework. Briefings in Bioinformatics. 26(4).

Wang, Dandan, et al.. (2024). Exploring spatio-temporal dynamics for enhanced wind turbine condition monitoring. Mechanical Systems and Signal Processing. 223. 111841–111841. 10 indexed citations

Shi, Yihui, et al.. (2024). Protein phosphorylation and kinases: Potential therapeutic targets in necroptosis. European Journal of Pharmacology. 970. 176508–176508. 8 indexed citations

Shi, Shaohua, Li Fu, Jiacai Yi, et al.. (2024). ChemFH: an integrated tool for screening frequent false positives in chemical biology and drug discovery. Nucleic Acids Research. 52(W1). W439–W449.

Yi, Jiacai, Ziyi Yang, Wentao Zhao, et al.. (2024). ChemMORT: an automatic ADMET optimization platform using deep learning and multi-objective particle swarm optimization. Briefings in Bioinformatics. 25(2). 10 indexed citations

Chen, Caiming, Kunmei Lai, Chengkun Wu, et al.. (2024). GSDMD and GSDME synergy in the transition of acute kidney injury to chronic kidney disease. Nephrology Dialysis Transplantation. 39(8). 1344–1359. 15 indexed citations

10.

Wu, Fan, Caiming Chen, Chengkun Wu, et al.. (2024). Caspase-11/GSDMD contributes to the progression of hyperuricemic nephropathy by promoting NETs formation. Cellular and Molecular Life Sciences. 81(1). 114–114. 15 indexed citations

11.

Xie, Yu, Jing Yu, Chengkun Wu, et al.. (2024). LINC00173 silence and estrone supply suppress ER⁺ breast cancer by estrogen receptor α degradation and LITAF activation. Cancer Science. 115(7). 2318–2332. 2 indexed citations

12.

Jiang, Lei, Chengkun Wu, Yao Lu, Qiuxia Dong, & Guohua Wu. (2023). Effect of CeO₂ NPs on stability of regenerated silk fibroin against UV‐aging. Journal of Applied Polymer Science. 140(17). 2 indexed citations

13.

Yi, Jiacai, et al.. (2022). ABC-Net: a divide-and-conquer based deep learning architecture for SMILES recognition from molecular images. Briefings in Bioinformatics. 23(2). 15 indexed citations

14.

Kuang, Yun, Yaxin Liu, Qi Pei, et al.. (2022). Long Short-Term Memory Network for Development and Simulation of Warfarin Dosing Model Based on Time Series Anticoagulant Data. Frontiers in Cardiovascular Medicine. 9. 881111–881111. 5 indexed citations

15.

Xiong, Guo‐Li, Zhenhua Wu, Jiacai Yi, et al.. (2021). ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties. Nucleic Acids Research. 49(W1). W5–W14. 1709 indexed citations breakdown →

16.

Wu, Chengkun, et al.. (2021). Mining microbe–disease interactions from literature via a transfer learning model. BMC Bioinformatics. 22(1). 432–432. 14 indexed citations

17.

Li, Yaqian, et al.. (2020). Quality of oral anticoagulation control in Chinese patients with non-valvular atrial fibrillation: a prospective controlled study. Current Medical Research and Opinion. 36(9). 1433–1439. 4 indexed citations

18.

Wu, Chengkun, Shaowei Zhang, Lei Peng, et al.. (2019). GTX.Digest.VCF: an online NGS data interpretation system based on intelligent gene ranking and large-scale text mining. BMC Medical Genomics. 12(S8). 193–193. 5 indexed citations

19.

Wang, Wei, Xi Yang, Canqun Yang, et al.. (2017). Dependency-based long short term memory network for drug-drug interaction extraction. BMC Bioinformatics. 18(S16). 578–578. 54 indexed citations

20.

Wu, Chengkun, Jean‐Marc Schwartz, Georg Brabant, & Goran Nenadić. (2014). Molecular profiling of thyroid cancer subtypes using large-scale text mining. BMC Medical Genomics. 7(S3). S3–S3. 10 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.

Explore authors with similar magnitude of impact