Tom Kurtzman

3.5k citations
27 papers · 2.1k · 1 hit paper · h-index 15

Impact in

Papers in

Tom Kurtzman

26 papers receiving 2.0k citations

Tom Kurtzman's Hit Papers

AmberTools 2023 · 1.2k citations
1.2k0+1+2Years since publication2505007501000

Peers

Tom Kurtzman
Comparison fields: 5 of 137
  • Computational Theory and Mathematics 511
  • Molecular Biology 1.3k
  • Physical and Theoretical Chemistry 103
  • Materials Chemistry 366
  • Spectroscopy 124
Replace Viet Hoang Man with:
Viet Hoang Man United States
Tyler Luchko United States
Ramu Anandakrishnan United States
Francesco Colizzi Italy
Boris H. Aguilar United States
David J. Huggins United States
Qi-Shi Du China
Kellon A. A. Belfon United States
Callum J. Dickson United States
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Citations per year

Countries citing papers authored by Tom Kurtzman

Since Specialization
Citations

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

Fields of papers citing papers by Tom Kurtzman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1
AmberTools
Hit paper breakdown →
20231163
2 2019190
3 2014120
4 201695
5
Amber 2021: Reference Manual
202183
6 201764
7 201747
8 201941
9 201537
10 201631
11 201828
12 201528
13 201528
14 202127
15 201926
16 201615
17 202212
18 201911
19 202010
20 20189

About Tom Kurtzman

Tom Kurtzman is a scholar working on Computational Theory and Mathematics, Molecular Biology, Atomic and Molecular Physics, and Optics, Physical and Theoretical Chemistry and Pharmaceutical Science, having authored 27 papers that have together received 2.1k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (18 papers), Computational Drug Discovery Methods (9 papers), Spectroscopy and Quantum Chemical Studies (7 papers), Enzyme Structure and Function (4 papers), Drug Solubulity and Delivery Systems (2 papers), Receptor Mechanisms and Signaling (2 papers), Granular flow and fluidized beds (1 paper) and Chemical and Physical Properties in Aqueous Solutions (1 paper). The work is most often cited by research in Computational Theory and Mathematics (511 citations), Molecular Biology (1.3k citations), Physical and Theoretical Chemistry (103 citations), Materials Chemistry (366 citations) and Spectroscopy (124 citations). Tom Kurtzman has collaborated with scholars based in United States, South Korea and Austria. Frequent co-authors include Michael K. Gilson, Anthony Cruz, Crystal N. Nguyen, Steven Ramsey, Lieyang Chen, José S. Duca, Ross C. Walker, Callum J. Dickson, Viktor Horn̆ák and David Ryan Koes. Their work appears in journals such as Journal of Chemical Theory and Computation, Journal of Computer-Aided Molecular Design, Journal of Chemical Information and Modeling, PLoS ONE and The Journal of Physical Chemistry B.

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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