Jason Swails

17.5k citations
19 papers · 10.3k indexed · 4 hit papers · h-index 15

Jason Swails

19 papers receiving 10.3k citations

Hit Papers

OpenMM 7: Rapid development of high performance algorith...1.7k201220262016202110002.0k3.0k

Peers

Jason Swails
Comparison fields: 5 of 161
  • Molecular Biology 7.2k
  • Computational Theory and Mathematics 1.6k
  • Spectroscopy 717
  • Toxicology 138
  • Infectious Diseases 719
Replace Koushik Kasavajhala with:
Koushik Kasavajhala United States
Lauren Wickstrom United States
Tai‐Sung Lee United States
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Citations per field
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Koushik Kasavajhala · 1×
Citations per year

Countries citing papers authored by Jason Swails

Since Specialization
Citations

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

Fields of papers citing papers by Jason Swails

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jason Swails. 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 Jason Swails. The network helps show where Jason Swails may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Jason Swails, 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 Jason Swails Line = papers co-authored together Jason Swails links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 201927
2 20181
3 201817
4
OpenMM 7: Rapid development of high performance algorithms for molecular dynamicsbreakdown →
20171736
5 20178
6 2016242
7 201617
8
MDTraj: A Modern Open Library for the Analysis of Molecular Dynamics Trajectoriesbreakdown →
20151537
9 201551
10 201532
11
CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Fieldbreakdown →
20152803
12 2014213
13 2013109
14 20132
15 201342
16 201287
17
MMPBSA.py: An Efficient Program for End-State Free Energy Calculationsbreakdown →
20123339
18 20119
19 200930

About Jason Swails

Jason Swails is a scholar working on Structural Biology, Spectroscopy and Molecular Biology, having authored 19 papers that have together received 10.3k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (12 papers), DNA and Nucleic Acid Chemistry (6 papers), Spectroscopy and Quantum Chemical Studies (4 papers), RNA and protein synthesis mechanisms (4 papers), Enzyme Structure and Function (3 papers), Mass Spectrometry Techniques and Applications (3 papers), Bacterial Genetics and Biotechnology (2 papers) and Photosynthetic Processes and Mechanisms (2 papers). The work is most often cited by research in Molecular Biology (7.2k citations), Computational Theory and Mathematics (1.6k citations) and Spectroscopy (717 citations). Jason Swails has collaborated with scholars based in United States, China and Netherlands. Frequent co-authors include Adrián E. Roitberg, Bill R. Miller, T. Dwight McGee, Holger Gohlke, Nadine Homeyer, Vijay S. Pande, Peter Eastman, Robert T. McGibbon, Lee‐Ping Wang and Matthew P. Harrigan. Their work appears in journals such as Journal of Chemical Theory and Computation, Acta Crystallographica Section D Structural Biology, Acta Crystallographica Section A Foundations and Advances, Journal of Biomolecular NMR and PLoS Computational Biology.

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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