Mark Mackey
Impact in
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- Computational Drug Discovery Methods
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- Protein Structure and Dynamics
- Chemical Synthesis and Analysis
- Receptor Mechanisms and Signaling
Papers in
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- Protein Structure and Dynamics 7
- Bioinformatics and Genomic Networks 2
- Chemical Synthesis and Analysis 2
- Insect Resistance and Genetics 1
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- Computational Drug Discovery Methods 11
- Co-authors
- Sally Rose (2 shared papers)Matthias R. Bauer (1 shared paper)James L. Melville (2 shared papers)Julien Michel (3 shared papers)Paolo Tosco (2 shared papers)Antonia S. J. S. Mey (2 shared papers)Maximilian Kühn (1 shared paper)Stuart Firth‐Clark (1 shared paper)
- Journals
- Journal of Chemical Information and Modeling (7 papers)Journal of the American Chemical Society (1 paper)Journal of Medicinal Chemistry (1 paper)ACS Medicinal Chemistry Letters (1 paper)Expert Opinion on Drug Discovery (1 paper)
- Partner nations
- United KingdomUnited States
In The Last Decade
Mark Mackey
13 papers receiving 934 citations
Peers
Comparison fields: 5 of 115
- Computational Theory and Mathematics 466
- Molecular Biology 589
- Pharmacology 103
- Pharmacology 44
- Organic Chemistry 147
Countries citing papers authored by Mark Mackey
This map shows the geographic impact of Mark Mackey'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 Mark Mackey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Mackey more than expected).
Fields of papers citing papers by Mark Mackey
This network shows the impact of papers produced by Mark Mackey. 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 Mark Mackey. The network helps show where Mark Mackey may publish in the future.
Co-authors
The 25 scholars most cited alongside Mark Mackey, 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 | 2006 | 329 | |
| 2 | 2020 | 163 | |
| 3 | 2019 | 132 | |
| 4 | 2008 | 106 | |
| 5 | 2007 | 63 | |
| 6 | 2009 | 54 | |
| 7 | 2020 | 41 | |
| 8 | 2022 | 37 | |
| 9 | 2023 | 29 | |
| 10 | 2022 | 8 | |
| 11 | 2004 | 7 | |
| 12 | 2025 | 5 | |
| 13 | 2014 | 3 | |
| 14 | 2025 | 1 |
About Mark Mackey
Mark Mackey is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Pharmacology and Information Systems, having authored 14 papers that have together received 978 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (11 papers), Protein Structure and Dynamics (7 papers), Machine Learning in Materials Science (3 papers), Enzyme Structure and Function (2 papers), Bioinformatics and Genomic Networks (2 papers), Chemical Synthesis and Analysis (2 papers), Microbial Natural Products and Biosynthesis (2 papers) and Insect Resistance and Genetics (1 paper). The work is most often cited by research in Computational Theory and Mathematics (466 citations), Molecular Biology (589 citations), Pharmacology (103 citations), Pharmacology (44 citations) and Organic Chemistry (147 citations). Mark Mackey has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include Sally Rose, Matthias R. Bauer, James L. Melville, Julien Michel, Paolo Tosco, Antonia S. J. S. Mey, Maximilian Kühn, Stuart Firth‐Clark, Jeremy G. Vinter and Christopher A. Hunter. Their work appears in journals such as Journal of Chemical Information and Modeling, Journal of the American Chemical Society, Journal of Medicinal Chemistry, ACS Medicinal Chemistry Letters and Expert Opinion on Drug Discovery.
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.