Scott Boyer
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods 31
- Pharmacology top 1%
- Pharmacogenetics and Drug Metabolism 8
- Toxicology top 5%
- Molecular Biology top 10%
- Metabolomics and Mass Spectrometry Studies 6
- Biomedical Text Mining and Ontologies 5
- Spectroscopy top 5%
- Analytical Chemistry and Chromatography 9
-
- Machine Learning in Materials Science 9
-
- Chemistry and Chemical Engineering 4
-
- Drug Transport and Resistance Mechanisms 4
- Co-authors
- Lars CarlssonUlf NorinderMartin EklundCatrin Hasselgren ArnbyJohn E. MulletBrian A. LarkinsJames M. SmithRobert C. Glen
- Journals
- Journal of Chemical Information and Modeling (11 papers)The Plant Cell (4 papers)Journal of Computer-Aided Molecular Design (3 papers)
- Partner nations
- SwedenUnited StatesUnited Kingdom
In The Last Decade
Scott Boyer
67 papers receiving 2.2k citations
Peers
Comparison fields: 5 of 155
- Computational Theory and Mathematics 1.1k
- Pharmacology 333
- Toxicology 57
- Molecular Biology 1.0k
- Spectroscopy 237
Countries citing papers authored by Scott Boyer
This map shows the geographic impact of Scott Boyer'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 Scott Boyer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Scott Boyer more than expected).
Fields of papers citing papers by Scott Boyer
This network shows the impact of papers produced by Scott Boyer. 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 Scott Boyer. The network helps show where Scott Boyer may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Scott Boyer, 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 | 2025 | 4 | |
| 2 | 2023 | 7 | |
| 3 | 2017 | 33 | |
| 4 | 2016 | 66 | |
| 5 | 2013 | 11 | |
| 6 | the Eu-adr Alliance: A Federated Collaborative Framework for Drug Safety Studies : 667. | 2012 | 1 |
| 7 | 2012 | 23 | |
| 8 | 2011 | 34 | |
| 9 | 2010 | 62 | |
| 10 | 2009 | 85 | |
| 11 | 2007 | 52 | |
| 12 | 2007 | 19 | |
| 13 | 2007 | 4 | |
| 14 | 2007 | 35 | |
| 15 | 2005 | 28 | |
| 16 | 2005 | 79 | |
| 17 | 2003 | 42 | |
| 18 | 2002 | 46 | |
| 19 | 1997 | 8 | |
| 20 | 1988 | 16 |
About Scott Boyer
Scott Boyer is a scholar working on Computational Theory and Mathematics, Pharmacology and Toxicology, having authored 69 papers that have together received 2.3k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (31 papers), Analytical Chemistry and Chromatography (9 papers), Machine Learning in Materials Science (9 papers), Pharmacogenetics and Drug Metabolism (8 papers), Metabolomics and Mass Spectrometry Studies (6 papers), Biomedical Text Mining and Ontologies (5 papers), Chemistry and Chemical Engineering (4 papers) and Drug Transport and Resistance Mechanisms (4 papers). The work is most often cited by research in Computational Theory and Mathematics (1.1k citations), Pharmacology (333 citations) and Toxicology (57 citations). Scott Boyer has collaborated with scholars based in Sweden, United States and United Kingdom. Frequent co-authors include Lars Carlsson, Ulf Norinder, Martin Eklund, Catrin Hasselgren Arnby, John E. Mullet, Brian A. Larkins, James M. Smith, Robert C. Glen, Ann‐Charlotte Egnell and Brian Houston. Their work appears in journals such as Journal of Chemical Information and Modeling, The Plant Cell, Journal of Computer-Aided Molecular Design, Pharmacoepidemiology and Drug Safety and Regulatory Toxicology and Pharmacology.
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.