David Ryan Koes

8.4k citations
73 papers · 3.7k indexed · 3 hit papers · h-index 25
Topics
Computational Drug Discovery Methods (36 papers)Protein Structure and Dynamics (18 papers)Machine Learning in Materials Science (16 papers)

In The Last Decade

David Ryan Koes

66 papers receiving 3.6k citations

Hit Papers

Lessons Learned in Empirical Scoring with smina from the ...2013202620172021201320212025200400600

Peers

David Ryan Koes
Comparison fields: 5 of 161
  • Molecular Biology 2.3k
  • Computational Theory and Mathematics 2.0k
  • Materials Chemistry 804
  • Organic Chemistry 482
  • Pharmacology 351
Replace Jacob D. Durrant with:
Jacob D. Durrant United States
Paul Czodrowski Germany
Michał Nowotka United Kingdom
Francis Atkinson United Kingdom
Trent E. Balius United States
Yurii S. Moroz Ukraine
Teague Sterling United States
Ryan G. Coleman United States
Herman van Vlijmen Belgium
Chang‐Yu Hsieh China
David Ryan Koes relative to Jacob D. Durrant United States Jacob D. Durrant's profile →
Citations per field
00.5×1.5×2.3×
Jacob D. Durrant · 1×
Citations per year

Countries citing papers authored by David Ryan Koes

Since Specialization
Citations

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

Fields of papers citing papers by David Ryan Koes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Ryan Koes. 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 David Ryan Koes. The network helps show where David Ryan Koes may publish in the future.

Co-authorship network of co-authors of David Ryan Koes

This figure shows the co-authorship network connecting the top 25 collaborators of David Ryan Koes. A scholar is included among the top collaborators of David Ryan Koes based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David Ryan Koes. David Ryan Koes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 4
3 0
4 22
5 8
6 0
7 6
8 1
9 1
10 62
11 3
12 10
13 169
14 13
15 11
16 1
17 18
18 4
19 79
20 68

About David Ryan Koes

David Ryan Koes is a scholar working on Computational Theory and Mathematics, Hardware and Architecture and Molecular Biology, having authored 73 papers that have together received 3.7k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (36 papers), Protein Structure and Dynamics (18 papers) and Machine Learning in Materials Science (16 papers). The work is most often cited by research in Computational Theory and Mathematics (2.0k citations), Molecular Biology (2.3k citations) and Pharmacology (351 citations). David Ryan Koes has collaborated with scholars based in United States, Germany and India. Frequent co-authors include Carlos J. Camacho, Jocelyn Sunseri, Matthew P. Baumgartner, Nicholas B. Rego, Paul Francoeur, Tomohide Masuda, Matthew Ragoza, Andrew T. McNutt, Rocco Meli and Rishal Aggarwal. Their work appears in journals such as Nucleic Acids Research, Journal of Biological Chemistry and Bioinformatics.

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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