Yankang Jing

752 total citations
13 papers, 476 citations indexed

About

Yankang Jing is a scholar working on Molecular Biology, Computational Theory and Mathematics and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Yankang Jing has authored 13 papers receiving a total of 476 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 7 papers in Computational Theory and Mathematics and 4 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Yankang Jing's work include Computational Drug Discovery Methods (7 papers), Receptor Mechanisms and Signaling (3 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). Yankang Jing is often cited by papers focused on Computational Drug Discovery Methods (7 papers), Receptor Mechanisms and Signaling (3 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). Yankang Jing collaborates with scholars based in United States, China and Australia. Yankang Jing's co-authors include Yuemin Bian, Lirong Wang, Ziheng Hu, Xiang‐Qun Xie, Franco Lombardo, Junmei Wang, Istvan Enyedy, David M. Peters, Alison Easter and Shifan Ma and has published in prestigious journals such as Pharmaceutical Research, Drug and Alcohol Dependence and Chemical Research in Toxicology.

In The Last Decade

Yankang Jing

12 papers receiving 471 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yankang Jing United States	9	231	217	82	56	36	13	476
Ziheng Hu United States	9	157 0.7×	191 0.9×	61 0.7×	31 0.6×	41 1.1×	16	465
Sunyoung Kwon South Korea	11	155 0.7×	245 1.1×	61 0.7×	19 0.3×	25 0.7×	30	544
Michael Farnum United States	12	125 0.5×	233 1.1×	47 0.6×	44 0.8×	16 0.4×	20	683
Thanh‐Hoang Nguyen‐Vo Vietnam	12	147 0.6×	273 1.3×	38 0.5×	35 0.6×	24 0.7×	26	465
Satoshi Niijima Japan	12	256 1.1×	356 1.6×	29 0.4×	66 1.2×	12 0.3×	19	505
Andreas Schüller Germany	17	206 0.9×	347 1.6×	66 0.8×	39 0.7×	23 0.6×	37	711
Guanyu Wang China	15	183 0.8×	312 1.4×	64 0.8×	21 0.4×	34 0.9×	58	768
Stefano Rensi United States	7	493 2.1×	375 1.7×	201 2.5×	62 1.1×	22 0.6×	10	804
Myeong‐Sang Yu South Korea	9	215 0.9×	216 1.0×	49 0.6×	40 0.7×	9 0.3×	14	423
Yifan Deng China	14	382 1.7×	401 1.8×	115 1.4×	46 0.8×	23 0.6×	37	718

Countries citing papers authored by Yankang Jing

Since Specialization

Citations

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

Fields of papers citing papers by Yankang Jing

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yankang Jing

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

All Works

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13 of 13 papers shown

Jing, Yankang, Terence F. McGuire, Jack Zhao, et al.. (2025). GraphDeep-hERG: Graph Neural Network PharmacoAnalytics for Assessing hERG-Related Cardiotoxicity. Pharmaceutical Research. 42(4). 579–591.

Jing, Yankang, Yuanyuan Xu, Terence F. McGuire, et al.. (2025). GCN-BBB: Deep Learning Blood-Brain Barrier (BBB) Permeability PharmacoAnalytics with Graph Convolutional Neural (GCN) Network. The AAPS Journal. 27(3). 73–73. 3 indexed citations

Ma, Shifan, et al.. (2022). Use of Solvent Mapping for Characterizing the Binding Site and for Predicting the Inhibition of the Human Ether-á-Go-Go-Related K⁺ Channel. Chemical Research in Toxicology. 35(8). 1359–1369. 1 indexed citations

Clegg, Lindsay E., Yankang Jing, Robert C. Penland, et al.. (2021). Cardiovascular and renal safety of metformin in patients with diabetes and moderate or severe chronic kidney disease: Observations from the EXSCEL and SAVOR‐TIMI 53 cardiovascular outcomes trials. Diabetes Obesity and Metabolism. 23(5). 1101–1110. 5 indexed citations

Xue, Ying, Ziheng Hu, Yankang Jing, et al.. (2020). Efficacy assessment of ticagrelor versus clopidogrel in Chinese patients with acute coronary syndrome undergoing percutaneous coronary intervention by data mining and machine‐learning decision tree approaches. Journal of Clinical Pharmacy and Therapeutics. 45(5). 1076–1086. 9 indexed citations

Jing, Yankang, Ziheng Hu, Ying Xue, et al.. (2019). Analysis of substance use and its outcomes by machine learning I. Childhood evaluation of liability to substance use disorder. Drug and Alcohol Dependence. 206. 107605–107605. 33 indexed citations

Chen, Maozi, Yankang Jing, Lirong Wang, Zhiwei Feng, & Xiang‐Qun Xie. (2019). DAKB-GPCRs: An Integrated Computational Platform for Drug Abuse Related GPCRs. Journal of Chemical Information and Modeling. 59(4). 1283–1289. 19 indexed citations

Hu, Ziheng, Yankang Jing, Ying Xue, et al.. (2019). Analysis of substance use and its outcomes by machine learning: II. Derivation and prediction of the trajectory of substance use severity. Drug and Alcohol Dependence. 206. 107604–107604. 18 indexed citations

Bian, Yuemin, et al.. (2019). Prediction of Orthosteric and Allosteric Regulations on Cannabinoid Receptors Using Supervised Machine Learning Classifiers. Molecular Pharmaceutics. 16(6). 2605–2615. 33 indexed citations

10.

Jing, Yankang, et al.. (2018). Deep Learning for Drug Design: an Artificial Intelligence Paradigm for Drug Discovery in the Big Data Era. The AAPS Journal. 20(3). 58–58. 225 indexed citations

11.

Bian, Yuemin, et al.. (2018). Computational systems pharmacology analysis of cannabidiol: a combination of chemogenomics-knowledgebase network analysis and integrated in silico modeling and simulation. Acta Pharmacologica Sinica. 40(3). 374–386. 37 indexed citations

12.

Lombardo, Franco & Yankang Jing. (2016). In Silico Prediction of Volume of Distribution in Humans. Extensive Data Set and the Exploration of Linear and Nonlinear Methods Coupled with Molecular Interaction Fields Descriptors. Journal of Chemical Information and Modeling. 56(10). 2042–2052. 41 indexed citations

13.

Jing, Yankang, et al.. (2015). In Silico Prediction of hERG Inhibition. Future Medicinal Chemistry. 7(5). 571–586. 52 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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