Steve Rees

969 total citations · 1 hit paper
9 papers, 495 citations indexed

About

Steve Rees is a scholar working on Molecular Biology, Computational Theory and Mathematics and Cellular and Molecular Neuroscience. According to data from OpenAlex, Steve Rees has authored 9 papers receiving a total of 495 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Computational Theory and Mathematics and 2 papers in Cellular and Molecular Neuroscience. Recurrent topics in Steve Rees's work include CRISPR and Genetic Engineering (4 papers), Computational Drug Discovery Methods (3 papers) and Receptor Mechanisms and Signaling (2 papers). Steve Rees is often cited by papers focused on CRISPR and Genetic Engineering (4 papers), Computational Drug Discovery Methods (3 papers) and Receptor Mechanisms and Signaling (2 papers). Steve Rees collaborates with scholars based in United Kingdom, United States and Sweden. Steve Rees's co-authors include James Matcham, Jerome T. Mettetal, Michael Snowden, J. Carl Barrett, Mark J. Anderton, Stefan Platz, Mark Fidock, Paul Morgan, Ulf G. Eriksson and Bengt Hamrén and has published in prestigious journals such as Nature Reviews Drug Discovery, British Journal of Pharmacology and Frontiers in Pharmacology.

In The Last Decade

Steve Rees

7 papers receiving 479 citations

Hit Papers

Impact of a five-dimensional framework on R&D product... 2018 2026 2020 2023 2018 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Impact of a five-dimensional framework on R&D productivity at AstraZeneca
    2018 271 citations Paul Morgan, Dean G. Brown et al. Nature Reviews Drug Discovery profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Steve Rees United Kingdom 6 257 97 87 56 46 9 495
Alexander R. Harmer United Kingdom 11 279 1.1× 103 1.1× 28 0.3× 95 1.7× 37 0.8× 19 514
Izumi V. Hinkson United States 9 340 1.3× 51 0.5× 49 0.6× 170 3.0× 69 1.5× 9 762
Adebayo Laniyonu Canada 15 223 0.9× 129 1.3× 30 0.3× 116 2.1× 66 1.4× 21 702
Ian L. Dale United Kingdom 16 455 1.8× 113 1.2× 60 0.7× 21 0.4× 28 0.6× 25 672
Sangeeta Raje United States 15 203 0.8× 79 0.8× 32 0.4× 54 1.0× 18 0.4× 26 535
Charles Mahoney United States 11 349 1.4× 90 0.9× 10 0.1× 78 1.4× 48 1.0× 36 656
Albert M. Kim United States 16 480 1.9× 162 1.7× 39 0.4× 74 1.3× 138 3.0× 27 1.2k
Caryn Lawrence United Kingdom 14 443 1.7× 118 1.2× 28 0.3× 28 0.5× 29 0.6× 19 762
Christopher M. Moxham United States 9 464 1.8× 72 0.7× 64 0.7× 116 2.1× 39 0.8× 10 677
Michelle M. Monasky Italy 21 704 2.7× 89 0.9× 24 0.3× 64 1.1× 38 0.8× 59 1.3k

Countries citing papers authored by Steve Rees

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Steve Rees

This figure shows the co-authorship network connecting the top 25 collaborators of Steve Rees. A scholar is included among the top collaborators of Steve Rees 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 Steve Rees. Steve Rees is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
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Winter, Matthew J., Yosuke Ono, Jonathan S. Ball, et al.. (2022). A Combined Human in Silico and CRISPR/Cas9-Mediated in Vivo Zebrafish Based Approach to Provide Phenotypic Data for Supporting Early Target Validation. Frontiers in Pharmacology. 13. 827686–827686. 6 indexed citations
4.
Morgan, Paul, Dean G. Brown, Simon Lennard, et al.. (2018). Impact of a five-dimensional framework on R&D productivity at AstraZeneca. Nature Reviews Drug Discovery. 17(3). 167–181. 271 indexed citations breakdown →
5.
Rees, Steve, Philip Gribbon, Karen Birmingham, William P. Janzen, & Garry Pairaudeau. (2015). Towards a hit for every target. Nature Reviews Drug Discovery. 15(1). 1–2. 21 indexed citations
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Southern, C., Jennifer M. Cook, Debra L. Taylor, et al.. (2013). Screening β-Arrestin Recruitment for the Identification of Natural Ligands for Orphan G-Protein–Coupled Receptors. SLAS DISCOVERY. 18(5). 599–609. 150 indexed citations
8.
Bevan, Nicola, Paul W. Hastwell, Patrick M. Eidam, et al.. (2012). The BlueScreen-384 Assay as an Indicator of Genotoxic Hazard Potential in Early-Stage Drug Discovery. SLAS DISCOVERY. 18(4). 441–452. 12 indexed citations
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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.

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