Chaokun Yan
Impact in
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- Computational Drug Discovery Methods
- Artificial Intelligence top 5%
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Machine Learning and Data Classification
Papers in
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- Bioinformatics and Genomic Networks 13
- Gene expression and cancer classification 11
- Machine Learning in Bioinformatics 9
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- AI in cancer detection 5
- Co-authors
- Huimin Luo (32 shared papers)Junwei Luo (24 shared papers)Jianlin Wang (20 shared papers)Jingjing Ma (5 shared papers)Ashutosh Patel (2 shared papers)Ge Zhang (7 shared papers)Ge Zhang (4 shared papers)Wenjuan Liang (7 shared papers)
- Journals
- Frontiers in Genetics (8 papers)BMC Bioinformatics (4 papers)Frontiers in Pharmacology (4 papers)Briefings in Bioinformatics (3 papers)Scientific Reports (1 paper)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Chaokun Yan
52 papers receiving 571 citations
Peers
Comparison fields: 5 of 96
- Computational Theory and Mathematics 116
- Artificial Intelligence 230
- Molecular Biology 258
- Health Information Management 15
- Computer Vision and Pattern Recognition 65
Countries citing papers authored by Chaokun Yan
This map shows the geographic impact of Chaokun 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 Chaokun Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chaokun Yan more than expected).
Fields of papers citing papers by Chaokun Yan
This network shows the impact of papers produced by Chaokun 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 Chaokun Yan. The network helps show where Chaokun Yan may publish in the future.
Co-authors
The 25 scholars most cited alongside Chaokun 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 57 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 107 | |
| 2 | 2020 | 67 | |
| 3 | 2024 | 34 | |
| 4 | 2019 | 28 | |
| 5 | 2021 | 27 | |
| 6 | 2023 | 25 | |
| 7 | 2022 | 24 | |
| 8 | 2018 | 22 | |
| 9 | 2019 | 18 | |
| 10 | 2019 | 17 | |
| 11 | 2022 | 17 | |
| 12 | 2021 | 16 | |
| 13 | 2021 | 15 | |
| 14 | 2022 | 12 | |
| 15 | 2021 | 12 | |
| 16 | 2020 | 11 | |
| 17 | 2022 | 11 | |
| 18 | 2013 | 11 | |
| 19 | 2021 | 10 | |
| 20 | 2020 | 8 |
About Chaokun Yan
Chaokun Yan is a scholar working on Molecular Biology, Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications and Information Systems, having authored 57 papers that have together received 584 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (13 papers), Bioinformatics and Genomic Networks (13 papers), Gene expression and cancer classification (11 papers), Machine Learning in Bioinformatics (9 papers), Distributed and Parallel Computing Systems (9 papers), Cloud Computing and Resource Management (6 papers), AI in cancer detection (5 papers) and Scientific Computing and Data Management (4 papers). The work is most often cited by research in Computational Theory and Mathematics (116 citations), Artificial Intelligence (230 citations), Molecular Biology (258 citations), Health Information Management (15 citations) and Computer Vision and Pattern Recognition (65 citations). Chaokun Yan has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Huimin Luo, Junwei Luo, Jianlin Wang, Jingjing Ma, Ashutosh Patel, Ge Zhang, Ge Zhang, Wenjuan Liang, Ge ZHANG and Wenxiu Wang. Their work appears in journals such as Frontiers in Genetics, BMC Bioinformatics, Frontiers in Pharmacology, Briefings in Bioinformatics and Scientific Reports.
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.