Matthew P. Repasky

20.6k citations
21 papers · 16.4k · 5 hit papers · h-index 18

Impact in

Papers in

Matthew P. Repasky

21 papers receiving 16.2k citations

Matthew P. Repasky's Hit Papers

Epik: p K a and Protonation State Prediction through Machine Learning 2023 · 166 citations
1660+7+14Years since publication2.5k5.0k7.5k

Peers

Matthew P. Repasky
Comparison fields: 5 of 161
  • Computational Theory and Mathematics 5.4k
  • Molecular Biology 9.6k
  • Toxicology 424
  • Organic Chemistry 3.6k
  • Pharmacology 1.8k
Replace Daniel T. Mainz with:
Daniel T. Mainz United States
Jay L. Banks United States
Leah L. Frye United States
William Lindstrom United States
Robert B. Murphy United States
Andrew R. Leach United Kingdom
Geoffrey Hutchison United States
G. Klebe Germany
Jeremy R. Greenwood United States
Holger Gohlke Germany
Matthew P. Repasky relative to Daniel T. Mainz United States Daniel T. Mainz's profile →
Citations per field
00.5×1.5×
Daniel T. Mainz · 1×
Citations per year

Countries citing papers authored by Matthew P. Repasky

Since Specialization
Citations

This map shows the geographic impact of Matthew P. Repasky'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 Matthew P. Repasky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew P. Repasky more than expected).

Fields of papers citing papers by Matthew P. Repasky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew P. Repasky. 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 Matthew P. Repasky. The network helps show where Matthew P. Repasky may publish in the future.

Co-authors

The 25 scholars most cited alongside Matthew P. Repasky, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Matthew P. Repasky Line = papers co-authored together Matthew P. Repasky links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Glide:  A New Approach for Rapid, Accurate Docking and Scoring. 1. Method and Assessment of Docking Accuracy
Hit paper breakdown →
20047949
2
Extra Precision Glide:  Docking and Scoring Incorporating a Model of Hydrophobic Enclosure for Protein−Ligand Complexes
Hit paper breakdown →
20065610
3
Integrated Modeling Program, Applied Chemical Theory (IMPACT)
Hit paper breakdown →
20051232
4 2002262
5
Efficient Exploration of Chemical Space with Docking and Deep Learning
Hit paper breakdown →
2021258
6 2007186
7
Epik: p K a and Protonation State Prediction through Machine Learning
Hit paper breakdown →
2023166
8 2012136
9 2016128
10 200371
11 202371
12 201669
13 200862
14 200359
15 200345
16 200343
17 200228
18 200221
19 199814
20 19997

About Matthew P. Repasky

Matthew P. Repasky is a scholar working on Computational Theory and Mathematics, Molecular Biology, Organic Chemistry, Atomic and Molecular Physics, and Optics and Physical and Theoretical Chemistry, having authored 21 papers that have together received 16.4k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (11 papers), Protein Structure and Dynamics (7 papers), Advanced Chemical Physics Studies (5 papers), Click Chemistry and Applications (2 papers), Spectroscopy and Quantum Chemical Studies (2 papers), Bioinformatics and Genomic Networks (2 papers), Crystallography and molecular interactions (2 papers) and Molecular Junctions and Nanostructures (2 papers). The work is most often cited by research in Computational Theory and Mathematics (5.4k citations), Molecular Biology (9.6k citations), Toxicology (424 citations), Organic Chemistry (3.6k citations) and Pharmacology (1.8k citations). Matthew P. Repasky has collaborated with scholars based in United States, India and Spain. Frequent co-authors include Richard A. Friesner, Robert B. Murphy, Daniel T. Mainz, Thomas A. Halgren, Jeremy R. Greenwood, Paul C. Sanschagrin, Leah L. Frye, Jay L. Banks, Mee Shelley and Jasna Klicić. Their work appears in journals such as Journal of Computational Chemistry, Journal of Medicinal Chemistry, Journal of Chemical Theory and Computation, Journal of Computer-Aided Molecular Design and Journal of the American Chemical Society.

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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