Steve Rees
Impact in
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- Computational Drug Discovery Methods
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- Neuropeptides and Animal Physiology
Papers in
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- CRISPR and Genetic Engineering 4
- RNA Interference and Gene Delivery 2
- Receptor Mechanisms and Signaling 2
- RNA and protein synthesis mechanisms 2
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- Computational Drug Discovery Methods 3
- Co-authors
- Jerome T. Mettetal (1 shared paper)Ulf G. Eriksson (1 shared paper)Menelas N. Pangalos (1 shared paper)Stefan Platz (1 shared paper)Bengt Hamrén (1 shared paper)Mark Fidock (1 shared paper)James Matcham (1 shared paper)J. Carl Barrett (1 shared paper)
- Journals
- eLife (2 papers)SLAS DISCOVERY (2 papers)Nature Reviews Drug Discovery (2 papers)Frontiers in Pharmacology (1 paper)British Journal of Pharmacology (1 paper)
- Partner nations
- United KingdomUnited StatesBrazil
In The Last Decade
Steve Rees
9 papers receiving 516 citations
Steve Rees's Hit Papers
Peers
Comparison fields: 5 of 105
- Computational Theory and Mathematics 100
- Cellular and Molecular Neuroscience 88
- Pharmacology 34
- Molecular Biology 264
- Biophysics 20
Countries citing papers authored by Steve Rees
This map shows the geographic impact of Steve Rees'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 Steve Rees with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steve Rees more than expected).
Fields of papers citing papers by Steve Rees
This network shows the impact of papers produced by Steve Rees. 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 Steve Rees. The network helps show where Steve Rees may publish in the future.
Co-authors
The 25 scholars most cited alongside Steve Rees, 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 | Impact of a five-dimensional framework on R&D productivity at AstraZeneca Hit paper breakdown → | 2018 | 302 |
| 2 | 2013 | 153 | |
| 3 | 1999 | 31 | |
| 4 | 2015 | 24 | |
| 5 | 2012 | 13 | |
| 6 | 2022 | 7 | |
| 7 | 2015 | 5 | |
| 8 | 2025 | 1 | |
| 9 | 2006 | 1 | |
| 10 | 2025 | 0 |
About Steve Rees
Steve Rees is a scholar working on Molecular Biology, Computational Theory and Mathematics, Cellular and Molecular Neuroscience, Computer Networks and Communications and Cardiology and Cardiovascular Medicine, having authored 10 papers that have together received 537 indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (4 papers), Computational Drug Discovery Methods (3 papers), RNA Interference and Gene Delivery (2 papers), Receptor Mechanisms and Signaling (2 papers), Neuropeptides and Animal Physiology (2 papers), RNA and protein synthesis mechanisms (2 papers), Oil and Gas Production Techniques (1 paper) and Statistical Methods in Clinical Trials (1 paper). The work is most often cited by research in Computational Theory and Mathematics (100 citations), Cellular and Molecular Neuroscience (88 citations), Pharmacology (34 citations), Molecular Biology (264 citations) and Biophysics (20 citations). Steve Rees has collaborated with scholars based in United Kingdom, United States and Brazil. Frequent co-authors include Jerome T. Mettetal, Ulf G. Eriksson, Menelas N. Pangalos, Stefan Platz, Bengt Hamrén, Mark Fidock, James Matcham, J. Carl Barrett, Simon Lennard and Ruth March. Their work appears in journals such as eLife, SLAS DISCOVERY, Nature Reviews Drug Discovery, Frontiers in Pharmacology and British Journal of 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.