Grover P. Miller
- Molecular Biology top 5%
- Pharmacology top 0.1%
- Computational Theory and Mathematics top 1%
- Organic Chemistry top 5%
- Oncology top 10%
- Co-authors
- F. Peter GuengerichS. Joshua SwamidassTyler B. HughesEric T. KoolNatilie HoseaStephen J. BenkovicChul‐Ho YunJessica H. Hartman
- Topics
- Pharmacogenetics and Drug Metabolism (56 papers)Computational Drug Discovery Methods (20 papers)Eicosanoids and Hypertension Pharmacology (16 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Chemical SocietyJournal of Biological Chemistry
- Partner nations
- United StatesNetherlandsSouth Korea
In The Last Decade
Grover P. Miller
96 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 132
- Molecular Biology 1.3k
- Pharmacology 1.1k
- Computational Theory and Mathematics 466
- Organic Chemistry 409
- Oncology 408
Countries citing papers authored by Grover P. Miller
This map shows the geographic impact of Grover P. Miller'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 Grover P. Miller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Grover P. Miller more than expected).
Fields of papers citing papers by Grover P. Miller
This network shows the impact of papers produced by Grover P. Miller. 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 Grover P. Miller. The network helps show where Grover P. Miller may publish in the future.
Co-authorship network of co-authors of Grover P. Miller
This figure shows the co-authorship network connecting the top 25 collaborators of Grover P. Miller. A scholar is included among the top collaborators of Grover P. Miller 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 Grover P. Miller. Grover P. Miller 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 | 8 | |
| 3 | 1 | |
| 4 | 6 | |
| 5 | 28 | |
| 6 | 14 | |
| 7 | 8 | |
| 8 | 16 | |
| 9 | 9 | |
| 10 | 8 | |
| 11 | 40 | |
| 12 | 4 | |
| 13 | Novel multi-mode ultra performance liquid chromatography–tandem mass spectrometry assay for profiling enantiomeric hydroxywarfarins and warfarin in human plasma | 1 |
| 14 | 38 | |
| 15 | 25 | |
| 16 | 14 | |
| 17 | 19 | |
| 18 | 12 | |
| 19 | 32 | |
| 20 | 6 |
About Grover P. Miller
Grover P. Miller is a scholar working on Pharmacology, Biochemistry and Computational Theory and Mathematics, having authored 97 papers that have together received 2.8k indexed citations. Recurring topics across this work include Pharmacogenetics and Drug Metabolism (56 papers), Computational Drug Discovery Methods (20 papers) and Eicosanoids and Hypertension Pharmacology (16 papers). The work is most often cited by research in Pharmacology (1.1k citations), Computational Theory and Mathematics (466 citations) and Biochemistry (199 citations). Grover P. Miller has collaborated with scholars based in United States, Netherlands and South Korea. Frequent co-authors include F. Peter Guengerich, S. Joshua Swamidass, Tyler B. Hughes, Eric T. Kool, Natilie Hosea, Stephen J. Benkovic, Chul‐Ho Yun, Jessica H. Hartman, Drew R. Jones and Stephen J. Benkovic. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Journal of Biological Chemistry.
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.