Gary J. Kapral

52.0k total citations · 4 hit papers
12 papers, 35.1k citations indexed

About

Gary J. Kapral is a scholar working on Molecular Biology, Materials Chemistry and Genetics. According to data from OpenAlex, Gary J. Kapral has authored 12 papers receiving a total of 35.1k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 6 papers in Materials Chemistry and 2 papers in Genetics. Recurrent topics in Gary J. Kapral's work include RNA and protein synthesis mechanisms (9 papers), Enzyme Structure and Function (6 papers) and Protein Structure and Dynamics (5 papers). Gary J. Kapral is often cited by papers focused on RNA and protein synthesis mechanisms (9 papers), Enzyme Structure and Function (6 papers) and Protein Structure and Dynamics (5 papers). Gary J. Kapral collaborates with scholars based in United States, United Kingdom and Czechia. Gary J. Kapral's co-authors include Jane S. Richardson, David Richardson, Vincent B. Chen, Jeffrey J. Headd, W.B. Arendall, Ian Davis, Laura W. Murray, Robert M. Immormino, D.A. Keedy and Randy J. Read and has published in prestigious journals such as Science, Journal of the American Chemical Society and Nucleic Acids Research.

In The Last Decade

Gary J. Kapral

11 papers receiving 34.9k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

PHENIX: a comprehensive Python-based system for macromolecular structure solution

2010 19.0k citations Paul D. Adams, Pavel V. Afonine et al. Acta Crystallographica Section D Biological Crystallography profile →
MolProbity: all-atom structure validation for macromolecular crystallography

2009 11.4k citations Vincent B. Chen, W.B. Arendall et al. Acta Crystallographica Section D Biological Crystallography profile →
MolProbity: all-atom contacts and structure validation for proteins and nucleic acids

2007 3.3k citations Ian Davis, Andrew Leaver‐Fay et al. Nucleic Acids Research profile →
The Phenix software for automated determination of macromolecular structures

2011 691 citations Paul D. Adams, Pavel V. Afonine et al. Methods profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Gary J. Kapral United States	11	25.5k	6.3k	4.1k	3.0k	3.0k	12	35.1k
Vincent B. Chen United States	16	25.3k 1.0×	6.3k 1.0×	4.0k 1.0×	3.0k 1.0×	3.0k 1.0×	22	35.1k
Nigel W. Moriarty United States	35	26.8k 1.1×	7.8k 1.2×	4.4k 1.1×	3.1k 1.0×	3.2k 1.1×	77	37.9k
Pavel V. Afonine United States	43	24.5k 1.0×	7.4k 1.2×	4.0k 1.0×	3.0k 1.0×	2.7k 0.9×	104	34.0k
Jeffrey J. Headd United States	17	28.2k 1.1×	7.4k 1.2×	4.5k 1.1×	3.2k 1.1×	3.3k 1.1×	20	39.1k
Li‐Wei Hung United States	30	21.2k 0.8×	5.5k 0.9×	3.6k 0.9×	2.5k 0.8×	2.5k 0.9×	68	29.4k
Martyn Winn United Kingdom	32	27.3k 1.1×	9.3k 1.5×	4.0k 1.0×	3.0k 1.0×	2.9k 1.0×	82	38.5k
Peter H. Zwart United States	31	20.6k 0.8×	6.0k 1.0×	3.4k 0.8×	2.4k 0.8×	2.3k 0.8×	60	28.6k
Ian Davis United States	23	20.8k 0.8×	5.3k 0.8×	3.1k 0.8×	2.4k 0.8×	2.4k 0.8×	56	28.9k
Roman A. Laskowski United Kingdom	51	33.9k 1.3×	8.4k 1.3×	4.0k 1.0×	3.0k 1.0×	3.5k 1.2×	109	47.1k
Nathaniel Echols United States	30	20.1k 0.8×	5.8k 0.9×	3.2k 0.8×	2.3k 0.8×	2.3k 0.8×	43	27.5k

Countries citing papers authored by Gary J. Kapral

Since Specialization

Citations

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

Fields of papers citing papers by Gary J. Kapral

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gary J. Kapral. 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 Gary J. Kapral. The network helps show where Gary J. Kapral may publish in the future.

Co-authorship network of co-authors of Gary J. Kapral

This figure shows the co-authorship network connecting the top 25 collaborators of Gary J. Kapral. A scholar is included among the top collaborators of Gary J. Kapral 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 Gary J. Kapral. Gary J. Kapral is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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12 of 12 papers shown

Kapral, Gary J., et al.. (2020). RNABC: forward kinematics to reduce all-atom steric clashes in RNA backbone. UNC Libraries.

Patwardhan, Neeraj N., Laura R. Ganser, Gary J. Kapral, et al.. (2017). Amiloride as a new RNA-binding scaffold with activity against HIV-1 TAR. MedChemComm. 8(5). 1022–1036. 63 indexed citations

Kapral, Gary J., et al.. (2016). Small Molecule-Based Pattern Recognition To Classify RNA Structure. Journal of the American Chemical Society. 139(1). 409–416. 51 indexed citations

Kapral, Gary J., Swati Jain, J. Noeske, et al.. (2014). New tools provide a second look at HDV ribozyme structure, dynamics and cleavage. Nucleic Acids Research. 42(20). 12833–12846. 29 indexed citations

Adams, Paul D., Pavel V. Afonine, G. Bunkóczi, et al.. (2011). The Phenix software for automated determination of macromolecular structures. Methods. 55(1). 94–106. 691 indexed citations breakdown →

Dunkle, J.A., Leyi Wang, Michael B. Feldman, et al.. (2011). Structures of the Bacterial Ribosome in Classical and Hybrid States of tRNA Binding. Science. 332(6032). 981–984. 304 indexed citations

Adams, Paul D., Pavel V. Afonine, G. Bunkóczi, et al.. (2010). PHENIX: a comprehensive Python-based system for macromolecular structure solution. Acta Crystallographica Section D Biological Crystallography. 66(2). 213–221. 18966 indexed citations breakdown →

Chen, Vincent B., W.B. Arendall, Jeffrey J. Headd, et al.. (2009). MolProbity: all-atom structure validation for macromolecular crystallography. Acta Crystallographica Section D Biological Crystallography. 66(1). 12–21. 11415 indexed citations breakdown →

Keedy, D.A., Christopher J. Williams, Jeffrey J. Headd, et al.. (2009). The other 90% of the protein: Assessment beyond the Cαs for CASP8 template‐based and high‐accuracy models. Proteins Structure Function and Bioinformatics. 77(S9). 29–49. 61 indexed citations

10.

Richardson, Jane S., Bohdan Schneider, Laura W. Murray, et al.. (2008). RNA backbone: Consensus all-angle conformers and modular string nomenclature (an RNA Ontology Consortium contribution). RNA. 14(3). 465–481. 202 indexed citations

11.

Kapral, Gary J., et al.. (2007). RNABC: forward kinematics to reduce all-atom steric clashes in RNA backbone. Journal of Mathematical Biology. 56(1-2). 253–278. 18 indexed citations

12.

Davis, Ian, Andrew Leaver‐Fay, Gary J. Kapral, et al.. (2007). MolProbity: all-atom contacts and structure validation for proteins and nucleic acids. Nucleic Acids Research. 35(Web Server). W375–W383. 3278 indexed citations breakdown →

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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