Kun‐Yi Hsin
Impact in
- Pharmacology top 5%
- Pharmacological Effects of Natural Compounds
Papers in
-
- Bioinformatics and Genomic Networks 5
- Protein Structure and Dynamics 2
- Gene Regulatory Network Analysis 2
- Microbial Metabolic Engineering and Bioproduction 2
- RNA and protein synthesis mechanisms 2
-
- Computational Drug Discovery Methods 5
- Co-authors
- Hiroaki Kitano (5 shared papers)Samik Ghosh (4 shared papers)Yoshiyuki Asai (3 shared papers)Yukiko Matsuoka (2 shared papers)Malcolm D. Walkinshaw (3 shared papers)Paul Taylor (2 shared papers)Yoshihiro Kawaoka (1 shared paper)Tokiko Watanabe (1 shared paper)
- Journals
- Nucleic Acids Research (3 papers)Animals (2 papers)Biochemical Pharmacology (1 paper)Journal of Applied Crystallography (1 paper)Nature Reviews Genetics (1 paper)
- Partner nations
- JapanTaiwanUnited Kingdom
In The Last Decade
Kun‐Yi Hsin
14 papers receiving 901 citations
Kun‐Yi Hsin's Hit Papers
Peers
Comparison fields: 5 of 117
- Pharmacology 111
- Complementary and alternative medicine 73
- Computational Theory and Mathematics 126
- Molecular Biology 444
- Pharmacology 84
Countries citing papers authored by Kun‐Yi Hsin
This map shows the geographic impact of Kun‐Yi Hsin'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 Kun‐Yi Hsin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun‐Yi Hsin more than expected).
Fields of papers citing papers by Kun‐Yi Hsin
This network shows the impact of papers produced by Kun‐Yi Hsin. 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 Kun‐Yi Hsin. The network helps show where Kun‐Yi Hsin may publish in the future.
Co-authors
The 25 scholars most cited alongside Kun‐Yi Hsin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Combining Machine Learning Systems and Multiple Docking Simulation Packages to Improve Docking Prediction Reliability for Network Pharmacology Hit paper breakdown → | 2013 | 420 |
| 2 | 2011 | 180 | |
| 3 | 2016 | 136 | |
| 4 | 2008 | 86 | |
| 5 | 2013 | 21 | |
| 6 | 2010 | 16 | |
| 7 | 2023 | 13 | |
| 8 | 2010 | 13 | |
| 9 | 2013 | 11 | |
| 10 | 2019 | 6 | |
| 11 | 2022 | 5 | |
| 12 | 2023 | 2 | |
| 13 | 2022 | 2 | |
| 14 | 2015 | 2 |
About Kun‐Yi Hsin
Kun‐Yi Hsin is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Pharmacology and Nutrition and Dietetics, having authored 14 papers that have together received 913 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (5 papers), Computational Drug Discovery Methods (5 papers), Enzyme Structure and Function (4 papers), Cholinesterase and Neurodegenerative Diseases (2 papers), Protein Structure and Dynamics (2 papers), Gene Regulatory Network Analysis (2 papers), Microbial Metabolic Engineering and Bioproduction (2 papers) and RNA and protein synthesis mechanisms (2 papers). The work is most often cited by research in Pharmacology (111 citations), Complementary and alternative medicine (73 citations), Computational Theory and Mathematics (126 citations), Molecular Biology (444 citations) and Pharmacology (84 citations). Kun‐Yi Hsin has collaborated with scholars based in Japan, Taiwan and United Kingdom. Frequent co-authors include Hiroaki Kitano, Samik Ghosh, Yoshiyuki Asai, Yukiko Matsuoka, Malcolm D. Walkinshaw, Yukiko Matsuoka, Paul Taylor, Yoshihiro Kawaoka, Tokiko Watanabe and Yujie Sheng. Their work appears in journals such as Nucleic Acids Research, Animals, Biochemical Pharmacology, Journal of Applied Crystallography and Nature Reviews Genetics.
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.