Michael J. Keiser
- Molecular Biology top 2%
- Computational Theory and Mathematics top 0.05%
- Pharmacology top 1%
- Pharmacology top 0.5%
- Organic Chemistry top 5%
- Co-authors
- Brian K. ShoichetJohn J. IrwinBryan L. RothPaul ErnsbergerBlaine N. ArmbrusterJérôme HertChristian LaggnerKangway V. Chuang
- Topics
- Computational Drug Discovery Methods (24 papers)Receptor Mechanisms and Signaling (9 papers)Protein Structure and Dynamics (7 papers)
- Journals
- NatureScienceNature Communications
- Partner nations
- United StatesSwitzerlandUnited Kingdom
In The Last Decade
Michael J. Keiser
49 papers receiving 5.4k citations
Hit Papers
Peers
Comparison fields: 5 of 164
- Molecular Biology 3.3k
- Computational Theory and Mathematics 3.1k
- Pharmacology 886
- Pharmacology 705
- Organic Chemistry 536
Countries citing papers authored by Michael J. Keiser
This map shows the geographic impact of Michael J. Keiser'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 Michael J. Keiser with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael J. Keiser more than expected).
Fields of papers citing papers by Michael J. Keiser
This network shows the impact of papers produced by Michael J. Keiser. 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 Michael J. Keiser. The network helps show where Michael J. Keiser may publish in the future.
Co-authorship network of co-authors of Michael J. Keiser
This figure shows the co-authorship network connecting the top 25 collaborators of Michael J. Keiser. A scholar is included among the top collaborators of Michael J. Keiser 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 Michael J. Keiser. Michael J. Keiser is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 5 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 9 | |
| 8 | 8 | |
| 9 | 22 | |
| 10 | 131 | |
| 11 | 22 | |
| 12 | 133 | |
| 13 | 90 | |
| 14 | 111 | |
| 15 | 92 | |
| 16 | 51 | |
| 17 | Predicting new molecular targets for known drugsbreakdown → | 1251 |
| 18 | 19 | |
| 19 | 29 | |
| 20 | Relating protein pharmacology by ligand chemistrybreakdown → | 1649 |
About Michael J. Keiser
Michael J. Keiser is a scholar working on Computational Theory and Mathematics, Biophysics and Equine, having authored 51 papers that have together received 5.5k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (24 papers), Receptor Mechanisms and Signaling (9 papers) and Protein Structure and Dynamics (7 papers). The work is most often cited by research in Computational Theory and Mathematics (3.1k citations), Pharmacology (705 citations) and Pharmacology (886 citations). Michael J. Keiser has collaborated with scholars based in United States, Switzerland and United Kingdom. Frequent co-authors include Brian K. Shoichet, John J. Irwin, Bryan L. Roth, Paul Ernsberger, Blaine N. Armbruster, Jérôme Hert, Christian Laggner, Kangway V. Chuang, Vincent Setola and Atheir I. Abbas. Their work appears in journals such as Nature, Science and Nature Communications.
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.