Ke Yan
Impact in
- Computational Mathematics top 5%
-
- Face and Expression Recognition
Papers in
-
- Machine Learning in Bioinformatics 23
- RNA and protein synthesis mechanisms 12
- Protein Structure and Dynamics 9
- Genomics and Phylogenetic Studies 6
- vaccines and immunoinformatics approaches 5
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- Face and Expression Recognition 6
- Co-authors
- Bin Liu (19 shared papers)Jie Wen (11 shared papers)Yong Xu (11 shared papers)Lunke Fei (5 shared papers)Xiaozhao Fang (4 shared papers)Hongwu Lv (8 shared papers)Yichen Guo (8 shared papers)Chenchen Li (1 shared paper)
- Journals
- Briefings in Bioinformatics (8 papers)Bioinformatics (5 papers)IEEE/ACM Transactions on Computational Biology and Bioinformatics (3 papers)BMC Biology (2 papers)IEEE Transactions on Neural Networks and Learning Systems (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Ke Yan
40 papers receiving 1.8k citations
Ke Yan's Hit Papers
Peers
Comparison fields: 5 of 115
- Computational Mathematics 30
- Computer Vision and Pattern Recognition 636
- Microbiology 163
- Media Technology 183
- Artificial Intelligence 420
Countries citing papers authored by Ke Yan
This map shows the geographic impact of Ke Yan'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 Ke Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ke Yan more than expected).
Fields of papers citing papers by Ke Yan
This network shows the impact of papers produced by Ke Yan. 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 Ke Yan. The network helps show where Ke Yan may publish in the future.
Co-authors
The 25 scholars most cited alongside Ke Yan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Robust Sparse Linear Discriminant Analysis Hit paper breakdown → | 2018 | 296 |
| 2 | 2020 | 183 | |
| 3 | sAMPpred-GAT: prediction of antimicrobial peptide by graph attention network and predicted peptide structure Hit paper breakdown → | 2022 | 151 |
| 4 | 2018 | 138 | |
| 5 | 2019 | 131 | |
| 6 | 2023 | 88 | |
| 7 | 2023 | 79 | |
| 8 | 2019 | 78 | |
| 9 | 2019 | 58 | |
| 10 | 2022 | 53 | |
| 11 | 2020 | 53 | |
| 12 | 2021 | 49 | |
| 13 | 2007 | 47 | |
| 14 | 2022 | 38 | |
| 15 | 2017 | 36 | |
| 16 | 2022 | 33 | |
| 17 | 2019 | 30 | |
| 18 | 2016 | 27 | |
| 19 | 2024 | 26 | |
| 20 | 2022 | 24 |
About Ke Yan
Ke Yan is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Media Technology, Computational Theory and Mathematics and Microbiology, having authored 40 papers that have together received 1.8k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (23 papers), RNA and protein synthesis mechanisms (12 papers), Protein Structure and Dynamics (9 papers), Face and Expression Recognition (6 papers), Genomics and Phylogenetic Studies (6 papers), vaccines and immunoinformatics approaches (5 papers), Remote-Sensing Image Classification (4 papers) and Antimicrobial Peptides and Activities (3 papers). The work is most often cited by research in Computational Mathematics (30 citations), Computer Vision and Pattern Recognition (636 citations), Microbiology (163 citations), Media Technology (183 citations) and Artificial Intelligence (420 citations). Ke Yan has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Bin Liu, Jie Wen, Yong Xu, Lunke Fei, Xiaozhao Fang, Hongwu Lv, Yichen Guo, Chenchen Li, Yan Chen and Jinrong Cui. Their work appears in journals such as Briefings in Bioinformatics, Bioinformatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics, BMC Biology and IEEE Transactions on Neural Networks and Learning Systems.
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.