Yaohang Li

5.8k total citations
144 papers, 3.8k citations indexed

About

Yaohang Li is a scholar working on Molecular Biology, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Yaohang Li has authored 144 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 80 papers in Molecular Biology, 45 papers in Computational Theory and Mathematics and 34 papers in Artificial Intelligence. Recurrent topics in Yaohang Li's work include Protein Structure and Dynamics (41 papers), Computational Drug Discovery Methods (35 papers) and Machine Learning in Bioinformatics (26 papers). Yaohang Li is often cited by papers focused on Protein Structure and Dynamics (41 papers), Computational Drug Discovery Methods (35 papers) and Machine Learning in Bioinformatics (26 papers). Yaohang Li collaborates with scholars based in United States, China and Canada. Yaohang Li's co-authors include Jianxin Wang, Min Li, Fang‐Xiang Wu, Mengyun Yang, Min Zeng, Yi Pan, Huimin Luo, Qichang Zhao, Fuhao Zhang and Ashraf Yaseen and has published in prestigious journals such as Journal of the American Chemical Society, Nucleic Acids Research and Nature Communications.

In The Last Decade

Yaohang Li

134 papers receiving 3.7k citations

Peers

Yaohang Li

CTM

Tatsuya Akutsu Japan

Jihong Guan China

Hiroshi Mamitsuka Japan

Lun Hu China

Elena Marchiori Netherlands

Shuigeng Zhou China

Nataša Pržulj United Kingdom

Ross D. King United Kingdom

Giancarlo Mauri Italy

Ola Spjuth Sweden

Tatsuya Akutsu Japan

Yaohang Li

7.4k ×3.1

1.4k ×0.9

CTM

884 ×1.7

390 ×0.8

364 ×0.9

Citations per year, relative to Yaohang Li Yaohang Li (= 1×) peers Tatsuya Akutsu

Countries citing papers authored by Yaohang Li

Since Specialization

Citations

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

Fields of papers citing papers by Yaohang Li

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yaohang Li

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

Adams, Douglas, et al.. (2025). VAIM-CFF: a variational autoencoder inverse mapper solution to Compton form factor extraction from deeply virtual exclusive reactions. The European Physical Journal C. 85(5). 3 indexed citations

Guo, Fei, Renchu Guan, Yaohang Li, et al.. (2025). Foundation models in bioinformatics. National Science Review. 12(4). nwaf028–nwaf028. 18 indexed citations

Wang, Meng, et al.. (2024). TripHLApan: predicting HLA molecules binding peptides based on triple coding matrix and transfer learning. Briefings in Bioinformatics. 25(3). 9 indexed citations

Li, Hong‐Dong, et al.. (2024). Identifying new cancer genes based on the integration of annotated gene sets via hypergraph neural networks. Bioinformatics. 40(Supplement_1). i511–i520. 6 indexed citations

Xu, Yunpei, Qilong Feng, Jiazhi Xia, et al.. (2024). scCAD: Cluster decomposition-based anomaly detection for rare cell identification in single-cell expression data. Nature Communications. 15(1). 7561–7561. 10 indexed citations

Battaglieri, M., Łukasz Bibrzycki, A. N. Hiller Blin, et al.. (2023). Toward a generative modeling analysis of CLAS exclusive 2π photoproduction. Physical review. D. 108(9). 5 indexed citations

Wang, Bin, et al.. (2023). DFHiC: a dilated full convolution model to enhance the resolution of Hi-C data. Bioinformatics. 39(5).

Zhao, Qichang, Guihua Duan, Mengyun Yang, et al.. (2022). AttentionDTA: Drug–Target Binding Affinity Prediction by Sequence-Based Deep Learning With Attention Mechanism. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 20(2). 852–863. 55 indexed citations

Zhao, Qichang, Mengyun Yang, Zhongjian Cheng, Yaohang Li, & Jianxin Wang. (2021). Biomedical Data and Deep Learning Computational Models for Predicting Compound-Protein Relations. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 19(4). 2092–2110. 24 indexed citations

10.

Yang, Mengyun, Yaohang Li, & Jianxin Wang. (2020). Feature and Nuclear Norm Minimization for Matrix Completion. IEEE Transactions on Knowledge and Data Engineering. 34(5). 2190–2199. 16 indexed citations

11.

Li, Min, et al.. (2020). DeepFrag-k: a fragment-based deep learning approach for protein fold recognition. BMC Bioinformatics. 21(S6). 203–203. 6 indexed citations

12.

Li, Min, et al.. (2019). A novel extended Pareto Optimality Consensus model for predicting essential proteins. Journal of Theoretical Biology. 480. 141–149. 9 indexed citations

13.

López‐Blanco, José Ramón, et al.. (2016). RCD+: Fast loop modeling server. Nucleic Acids Research. 44(W1). W395–W400. 44 indexed citations

14.

He, Wu, Xin Tian, Jiancheng Shen, & Yaohang Li. (2015). Understanding Mobile Banking Applications’ Security risks through Blog Mining and the Workflow Technology. International Conference on Information Systems.

15.

He, Wu, et al.. (2014). Teaching Information Security with Workflow Technology - A Case Study Approach. Journal of the Association for Information Systems. 25(3). 201–210. 5 indexed citations

16.

Li, Yaohang, et al.. (2008). A Sensor Information Framework for Integrating and Orchestrating Distributed Sensor Services.. Parallel and Distributed Processing Techniques and Applications. 857–862. 2 indexed citations

17.

Song, Yongduan, et al.. (2006). Using Grid Computing for Distributed Software Testing.. Parallel and Distributed Processing Techniques and Applications. 163(4). 931–936.

18.

Li, Yaohang, et al.. (2005). Path Planning for Unmanned Vehicles Using Ant Colony Optimization on a Dynamic Voronoi Diagram.. International Conference on Artificial Intelligence. 716–721. 5 indexed citations

19.

Li, Yaohang, et al.. (2004). A grid workflow-based Monte Carlo simulation environment. 12(3). 439–454. 1 indexed citations

20.

Li, Yaohang, Michael Mascagni, & Robert van Engelen. (2003). GCIMCA: A Globus and SPRNG Implementation of a Grid-Computing Infrastructure for Monte Carlo Applications.. Parallel and Distributed Processing Techniques and Applications. 71–76. 3 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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