Kaihsu Tai
- Molecular Biology
- Pharmacology top 5%
- Computational Theory and Mathematics top 2%
- Biomedical Engineering
- Materials Chemistry
- Co-authors
- Mark S.P. SansomJ. Andrew McCammonTongye ShenOliver BecksteinRichard H. HenchmanMarios PhilippopoulosUlf BörjessonPhilip W. Fowler
- Topics
- Protein Structure and Dynamics (7 papers)Computational Drug Discovery Methods (7 papers)Cholinesterase and Neurodegenerative Diseases (7 papers)
- Journals
- Journal of the American Chemical SocietyJournal of Biological ChemistryAccounts of Chemical Research
- Partner nations
- United KingdomUnited StatesFrance
In The Last Decade
Kaihsu Tai
28 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 101
- Molecular Biology 666
- Pharmacology 271
- Computational Theory and Mathematics 249
- Biomedical Engineering 144
- Materials Chemistry 130
Countries citing papers authored by Kaihsu Tai
This map shows the geographic impact of Kaihsu Tai'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 Kaihsu Tai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaihsu Tai more than expected).
Fields of papers citing papers by Kaihsu Tai
This network shows the impact of papers produced by Kaihsu Tai. 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 Kaihsu Tai. The network helps show where Kaihsu Tai may publish in the future.
Co-authorship network of co-authors of Kaihsu Tai
This figure shows the co-authorship network connecting the top 25 collaborators of Kaihsu Tai. A scholar is included among the top collaborators of Kaihsu Tai 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 Kaihsu Tai. Kaihsu Tai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 14 | |
| 2 | 10 | |
| 3 | 60 | |
| 4 | 20 | |
| 5 | 4 | |
| 6 | 24 | |
| 7 | BioSimGRID: Application to analysis of membrane protein simulations | 1 |
| 8 | 43 | |
| 9 | 29 | |
| 10 | A Web / Grid Portal Implementation of BioSimGrid: A Biomolecular Simulation Database | 2 |
| 11 | 80 | |
| 12 | 37 | |
| 13 | Efficient data storage and analysis for generic biomolecular simulation data | 2 |
| 14 | 39 | |
| 15 | 36 | |
| 16 | 49 | |
| 17 | 108 | |
| 18 | 26 | |
| 19 | 136 | |
| 20 | 8 |
About Kaihsu Tai
Kaihsu Tai is a scholar working on Computational Theory and Mathematics, Pharmacology and Information Systems and Management, having authored 28 papers that have together received 1.1k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (7 papers), Computational Drug Discovery Methods (7 papers) and Cholinesterase and Neurodegenerative Diseases (7 papers). The work is most often cited by research in Pharmacology (271 citations), Computational Theory and Mathematics (249 citations) and Molecular Biology (666 citations). Kaihsu Tai has collaborated with scholars based in United Kingdom, United States and France. Frequent co-authors include Mark S.P. Sansom, J. Andrew McCammon, Tongye Shen, Oliver Beckstein, Richard H. Henchman, Marios Philippopoulos, Ulf Börjesson, Philip W. Fowler, Jennifer M. Bui and Andrew Hung. Their work appears in journals such as Journal of the American Chemical Society, Journal of Biological Chemistry and Accounts of Chemical Research.
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.