Gary J. Kapral

52.0k citations
12 papers · 35.1k indexed · 4 hit papers · h-index 11

Gary J. Kapral

11 papers receiving 34.9k citations

Hit Papers

The Phenix software for automated determination of macrom...69120072026201320195.0k10.0k15.0k

Peers

Gary J. Kapral
Comparison fields: 5 of 168
  • Structural Biology 559
  • Molecular Biology 25.5k
  • Molecular Medicine 1.0k
  • Biotechnology 1.6k
  • Cell Biology 3.0k
Replace Vincent B. Chen with:
Vincent B. Chen United States
Jeffrey J. Headd United States
Nigel W. Moriarty United States
Martyn Winn United Kingdom
Peter H. Zwart United States
Li‐Wei Hung United States
Nathaniel Echols United States
Ian Davis United States
Pavel V. Afonine United States
Garib N. Murshudov United Kingdom
Gary J. Kapral relative to Vincent B. Chen United States Vincent B. Chen's profile →
Citations per field
00.5×1.5×
Vincent B. Chen · 1×
Citations per year

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

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

All Works

12 of 12 papers shown
#Work
1 20200
2 201763
3 201651
4 201429
5
The Phenix software for automated determination of macromolecular structuresbreakdown →
2011691
6 2011304
7
PHENIX: a comprehensive Python-based system for macromolecular structure solutionbreakdown →
201018966
8
MolProbity: all-atom structure validation for macromolecular crystallographybreakdown →
200911415
9 200961
10 2008202
11 200718
12
MolProbity: all-atom contacts and structure validation for proteins and nucleic acidsbreakdown →
20073278

About Gary J. Kapral

Gary J. Kapral is a scholar working on Molecular Biology, Materials Chemistry and Hepatology, having authored 12 papers that have together received 35.1k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (9 papers), Enzyme Structure and Function (6 papers), Protein Structure and Dynamics (5 papers), RNA modifications and cancer (4 papers), RNA Research and Splicing (4 papers), Bacterial Genetics and Biotechnology (2 papers), Hepatitis B Virus Studies (1 paper) and Hepatitis C virus research (1 paper). The work is most often cited by research in Structural Biology (559 citations), Molecular Biology (25.5k citations) and Molecular Medicine (1.0k citations). Gary J. Kapral has collaborated with scholars based in United States, United Kingdom and Czechia. Frequent 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 G. Bunkóczi. Their work appears in journals such as Nucleic Acids Research, Methods, Journal of Mathematical Biology, Journal of the American Chemical Society and Science.

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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