Eric T. Williams
Impact in
- Pharmacology top 5%
- Cholinesterase and Neurodegenerative Diseases
- Pharmacogenetics and Drug Metabolism
- Inflammatory mediators and NSAID effects
Papers in
-
- Protein Hydrolysis and Bioactive Peptides 2
- Metabolomics and Mass Spectrometry Studies 2
-
- Cholinesterase and Neurodegenerative Diseases 5
- Pharmacogenetics and Drug Metabolism 4
- Co-authors
- Steven Wrighton (5 shared papers)E.J. Perkins (4 shared papers)Y. Nancy Wong (2 shared papers)Jie Wang (1 shared paper)Christopher Patten (1 shared paper)Kenneth J. Ruterbories (2 shared papers)Yuewei Qian (3 shared papers)Nagy A. Farid (1 shared paper)
- Journals
- Drug Metabolism and Disposition (4 papers)Cancer Research (2 papers)Molecular Phylogenetics and Evolution (2 papers)Bioorganic & Medicinal Chemistry Letters (1 paper)Blood (1 paper)
- Partner nations
- United StatesSwitzerlandChina
In The Last Decade
Eric T. Williams
17 papers receiving 437 citations
Peers
Comparison fields: 5 of 82
- Pharmacology 120
- Pharmacology 166
- Toxicology 14
- Computational Theory and Mathematics 74
- Cardiology and Cardiovascular Medicine 81
Countries citing papers authored by Eric T. Williams
This map shows the geographic impact of Eric T. Williams'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 Eric T. Williams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric T. Williams more than expected).
Fields of papers citing papers by Eric T. Williams
This network shows the impact of papers produced by Eric T. Williams. 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 Eric T. Williams. The network helps show where Eric T. Williams may publish in the future.
Co-authors
The 25 scholars most cited alongside Eric T. Williams, 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 | 2011 | 110 | |
| 2 | 2008 | 109 | |
| 3 | 2011 | 62 | |
| 4 | 2004 | 40 | |
| 5 | 2010 | 28 | |
| 6 | 2007 | 22 | |
| 7 | 2011 | 21 | |
| 8 | 2004 | 15 | |
| 9 | 2013 | 8 | |
| 10 | 2020 | 8 | |
| 11 | 2022 | 5 | |
| 12 | 2007 | 4 | |
| 13 | 2020 | 4 | |
| 14 | 2021 | 3 | |
| 15 | 2023 | 3 | |
| 16 | 2019 | 1 | |
| 17 | Chimpanzee: A predictive model for the human cytochrome P450 3A subfamily | 2006 | 1 |
About Eric T. Williams
Eric T. Williams is a scholar working on Molecular Biology, Pharmacology, Pharmacology, Radiology, Nuclear Medicine and Imaging and Oncology, having authored 17 papers that have together received 444 indexed citations. Recurring topics across this work include Cholinesterase and Neurodegenerative Diseases (5 papers), Pharmacogenetics and Drug Metabolism (4 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), Toxin Mechanisms and Immunotoxins (3 papers), Computational Drug Discovery Methods (3 papers), HER2/EGFR in Cancer Research (2 papers), Protein Hydrolysis and Bioactive Peptides (2 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). The work is most often cited by research in Pharmacology (120 citations), Pharmacology (166 citations), Toxicology (14 citations), Computational Theory and Mathematics (74 citations) and Cardiology and Cardiovascular Medicine (81 citations). Eric T. Williams has collaborated with scholars based in United States, Switzerland and China. Frequent co-authors include Steven Wrighton, E.J. Perkins, Y. Nancy Wong, Jie Wang, Christopher Patten, Kenneth J. Ruterbories, Yuewei Qian, Nagy A. Farid, Henry W. Strobel and G. Douglas Ponsler. Their work appears in journals such as Drug Metabolism and Disposition, Cancer Research, Molecular Phylogenetics and Evolution, Bioorganic & Medicinal Chemistry Letters and Blood.
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.