Mark McGann
Impact in
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- Computational Drug Discovery Methods
- Molecular Biology top 10%
- Protein Structure and Dynamics
- Receptor Mechanisms and Signaling
- Chemical Synthesis and Analysis
Papers in
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- Protein Structure and Dynamics 3
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- Computational Drug Discovery Methods 4
- Co-authors
- Anthony Nicholls (2 shared papers)Harold R. Almond (1 shared paper)Frank K. Brown (1 shared paper)Jennifer Grant (1 shared paper)Daniel J. Lacks (5 shared papers)Istvan Enyedy (3 shared papers)Shifan Ma (2 shared papers)Yankang Jing (1 shared paper)
- Journals
- The Journal of Physical Chemistry B (2 papers)Journal of Computer-Aided Molecular Design (2 papers)Journal of Chemical Information and Modeling (1 paper)The Journal of Chemical Physics (1 paper)Macromolecules (1 paper)
- Partner nations
- United StatesRussiaUnited Kingdom
In The Last Decade
Mark McGann
11 papers receiving 1.4k citations
Mark McGann's Hit Papers
Peers
Comparison fields: 5 of 114
- Computational Theory and Mathematics 581
- Molecular Biology 865
- Organic Chemistry 300
- Toxicology 29
- Pharmacology 136
Countries citing papers authored by Mark McGann
This map shows the geographic impact of Mark McGann'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 McGann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark McGann more than expected).
Fields of papers citing papers by Mark McGann
This network shows the impact of papers produced by Mark McGann. 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 McGann. The network helps show where Mark McGann may publish in the future.
Co-authors
The 9 scholars most cited alongside Mark McGann, 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 | FRED Pose Prediction and Virtual Screening Accuracy Hit paper breakdown → | 2011 | 598 |
| 2 | 2012 | 382 | |
| 3 | 2002 | 372 | |
| 4 | 1999 | 15 | |
| 5 | 2015 | 13 | |
| 6 | 2021 | 7 | |
| 7 | 1999 | 7 | |
| 8 | 1999 | 6 | |
| 9 | 1998 | 4 | |
| 10 | 1998 | 2 | |
| 11 | 2022 | 1 |
About Mark McGann
Mark McGann is a scholar working on Molecular Biology, Computational Theory and Mathematics, Polymers and Plastics, Materials Chemistry and Mechanics of Materials, having authored 11 papers that have together received 1.4k indexed citations. Recurring topics across this work include Polymer crystallization and properties (4 papers), Computational Drug Discovery Methods (4 papers), Protein Structure and Dynamics (3 papers), Enzyme Structure and Function (2 papers), Mechanical Behavior of Composites (2 papers), Phase Equilibria and Thermodynamics (2 papers), Rheology and Fluid Dynamics Studies (2 papers) and Imbalanced Data Classification Techniques (1 paper). The work is most often cited by research in Computational Theory and Mathematics (581 citations), Molecular Biology (865 citations), Organic Chemistry (300 citations), Toxicology (29 citations) and Pharmacology (136 citations). Mark McGann has collaborated with scholars based in United States, Russia and United Kingdom. Frequent co-authors include Anthony Nicholls, Harold R. Almond, Frank K. Brown, Jennifer Grant, Daniel J. Lacks, Istvan Enyedy, Shifan Ma, Yankang Jing and Sándor Vajda. Their work appears in journals such as The Journal of Physical Chemistry B, Journal of Computer-Aided Molecular Design, Journal of Chemical Information and Modeling, The Journal of Chemical Physics and Macromolecules.
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.