Mark McGann
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- Computational Drug Discovery Methods 4
- Molecular Biology top 10%
- Protein Structure and Dynamics 3
- Organic Chemistry top 10%
- Toxicology top 10%
- Pharmacology top 10%
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- Polymer crystallization and properties 4
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- Rheology and Fluid Dynamics Studies 2
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- Mechanical Behavior of Composites 2
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- Enzyme Structure and Function 2
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- Phase Equilibria and Thermodynamics 2
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- Advanced Physical and Chemical Molecular Interactions 1
- Co-authors
- Anthony NichollsHarold R. AlmondJennifer GrantFrank K. BrownDaniel J. LacksIstvan EnyedyShifan MaYankang Jing
- Journals
- Journal of Computer-Aided Molecular Design (2 papers)The Journal of Physical Chemistry B (2 papers)Macromolecules (1 paper)
- Partner nations
- United StatesUnited KingdomRussia
In The Last Decade
Mark McGann
11 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Computational Theory and Mathematics 600
- Molecular Biology 893
- Organic Chemistry 303
- Toxicology 31
- Pharmacology 144
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-authorship network
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 | 2022 | 1 | |
| 2 | 2021 | 6 | |
| 3 | 2015 | 13 | |
| 4 | 2012 | 372 | |
| 5 | FRED Pose Prediction and Virtual Screening Accuracybreakdown → | 2011 | 587 |
| 6 | 2002 | 371 | |
| 7 | 1999 | 15 | |
| 8 | 1999 | 6 | |
| 9 | 1999 | 7 | |
| 10 | 1998 | 2 | |
| 11 | 1998 | 4 |
About Mark McGann
Mark McGann is a scholar working on Fluid Flow and Transfer Processes, Polymers and Plastics, Computational Theory and Mathematics, Physical and Theoretical Chemistry and Analytical Chemistry, having authored 11 papers that have together received 1.4k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (4 papers), Polymer crystallization and properties (4 papers), Protein Structure and Dynamics (3 papers), Rheology and Fluid Dynamics Studies (2 papers), Mechanical Behavior of Composites (2 papers), Enzyme Structure and Function (2 papers), Phase Equilibria and Thermodynamics (2 papers) and Advanced Physical and Chemical Molecular Interactions (1 paper). The work is most often cited by research in Computational Theory and Mathematics (600 citations), Molecular Biology (893 citations), Organic Chemistry (303 citations), Toxicology (31 citations) and Pharmacology (144 citations). Mark McGann has collaborated with scholars based in United States, United Kingdom and Russia. Frequent co-authors include Anthony Nicholls, Harold R. Almond, Jennifer Grant, Frank K. Brown, Daniel J. Lacks, Istvan Enyedy, Shifan Ma, Yankang Jing and Sándor Vajda. Their work appears in journals such as Journal of Computer-Aided Molecular Design, The Journal of Physical Chemistry B, Macromolecules, Biopolymers and Chemical Research in Toxicology.
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.