Nigel Greene
- Computational Theory and Mathematics top 0.2%
- Computational Drug Discovery Methods 38
- Pharmacology top 0.5%
- Pharmacogenetics and Drug Metabolism 15
- Chemical Health and Safety top 5%
- Small Animals top 2%
- Animal testing and alternatives 10
- Spectroscopy top 5%
- Analytical Chemistry and Chromatography 7
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- Carcinogens and Genotoxicity Assessment 9
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- Chemistry and Chemical Engineering 5
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- Receptor Mechanisms and Signaling 4
- Metabolomics and Mass Spectrometry Studies 3
- Co-authors
- David A. PriceJulian BlaggTravis T. WagerRussell NavenPhilip N. JudsonCarol A. MarchantJ. J. LangowskiFalgun Shah
- Journals
- Regulatory Toxicology and Pharmacology (10 papers)Chemical Research in Toxicology (5 papers)Bioorganic & Medicinal Chemistry Letters (3 papers)
- Partner nations
- United StatesUnited KingdomSweden
In The Last Decade
Nigel Greene
54 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 147
- Computational Theory and Mathematics 1.3k
- Pharmacology 603
- Chemical Health and Safety 20
- Small Animals 153
- Spectroscopy 312
Countries citing papers authored by Nigel Greene
This map shows the geographic impact of Nigel Greene'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 Nigel Greene with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nigel Greene more than expected).
Fields of papers citing papers by Nigel Greene
This network shows the impact of papers produced by Nigel Greene. 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 Nigel Greene. The network helps show where Nigel Greene may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Nigel Greene, 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 | 0 | |
| 2 | 2024 | 28 | |
| 3 | 2024 | 18 | |
| 4 | 2024 | 1 | |
| 5 | 2022 | 46 | |
| 6 | 2022 | 9 | |
| 7 | 2022 | 2 | |
| 8 | 2021 | 59 | |
| 9 | 2020 | 29 | |
| 10 | 2017 | 25 | |
| 11 | 2016 | 43 | |
| 12 | 2015 | 32 | |
| 13 | 2014 | 22 | |
| 14 | 2014 | 26 | |
| 15 | 2012 | 23 | |
| 16 | 2012 | 62 | |
| 17 | 2010 | 53 | |
| 18 | 2009 | 12 | |
| 19 | 2009 | 107 | |
| 20 | 2006 | 91 |
About Nigel Greene
Nigel Greene is a scholar working on Computational Theory and Mathematics, Pharmacology and Small Animals, having authored 56 papers that have together received 2.7k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (38 papers), Pharmacogenetics and Drug Metabolism (15 papers), Animal testing and alternatives (10 papers), Carcinogens and Genotoxicity Assessment (9 papers), Analytical Chemistry and Chromatography (7 papers), Chemistry and Chemical Engineering (5 papers), Receptor Mechanisms and Signaling (4 papers) and Metabolomics and Mass Spectrometry Studies (3 papers). The work is most often cited by research in Computational Theory and Mathematics (1.3k citations), Pharmacology (603 citations) and Chemical Health and Safety (20 citations). Nigel Greene has collaborated with scholars based in United States, United Kingdom and Sweden. Frequent co-authors include David A. Price, Julian Blagg, Travis T. Wager, Russell Naven, Philip N. Judson, Carol A. Marchant, J. J. Langowski, Falgun Shah, Jason D. Hughes and Jens Loesel. Their work appears in journals such as Regulatory Toxicology and Pharmacology, Chemical Research in Toxicology, Bioorganic & Medicinal Chemistry Letters, Expert Opinion on Drug Metabolism & Toxicology and Toxicological Sciences.
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.