Jack Schonbrun
Impact in
- Immunology and Allergy top 5%
- Cell Adhesion Molecules Research
- Molecular Biology top 10%
- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- Machine Learning in Bioinformatics
- Lipid Membrane Structure and Behavior
- Receptor Mechanisms and Signaling
- Ion channel regulation and function
Papers in
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- Protein Structure and Dynamics 7
- RNA and protein synthesis mechanisms 3
- Genomics and Phylogenetic Studies 1
- Machine Learning in Bioinformatics 1
- Biochemical and Structural Characterization 1
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- Enzyme Structure and Function 5
- Co-authors
- David Baker (7 shared papers)Vladimir Yarov‐Yarovoy (1 shared paper)Patrick Barth (2 shared papers)Dylan Chivian (3 shared papers)William J. Wedemeyer (2 shared papers)David E. Kim (2 shared papers)Lars Malmström (2 shared papers)Carol A. Rohl (2 shared papers)
- Journals
- Proteins Structure Function and Bioinformatics (4 papers)Proceedings of the National Academy of Sciences (2 papers)Molecular Cell (1 paper)Current Opinion in Structural Biology (1 paper)
- Partner nations
- United States
In The Last Decade
Jack Schonbrun
8 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 88
- Immunology and Allergy 106
- Molecular Biology 858
- Cellular and Molecular Neuroscience 113
- Biophysics 31
- Sensory Systems 24
Countries citing papers authored by Jack Schonbrun
This map shows the geographic impact of Jack Schonbrun'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 Jack Schonbrun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jack Schonbrun more than expected).
Fields of papers citing papers by Jack Schonbrun
This network shows the impact of papers produced by Jack Schonbrun. 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 Jack Schonbrun. The network helps show where Jack Schonbrun may publish in the future.
Co-authors
The 19 scholars most cited alongside Jack Schonbrun, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2005 | 264 | |
| 2 | 2007 | 181 | |
| 3 | 2003 | 134 | |
| 4 | 2009 | 123 | |
| 5 | 2005 | 116 | |
| 6 | 2005 | 110 | |
| 7 | 2002 | 78 | |
| 8 | 2003 | 46 |
About Jack Schonbrun
Jack Schonbrun is a scholar working on Molecular Biology, Materials Chemistry, Spectroscopy, Cellular and Molecular Neuroscience and Genetics, having authored 8 papers that have together received 1.1k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (7 papers), Enzyme Structure and Function (5 papers), RNA and protein synthesis mechanisms (3 papers), Mass Spectrometry Techniques and Applications (2 papers), Genomics and Phylogenetic Studies (1 paper), Machine Learning in Bioinformatics (1 paper), Cell Adhesion Molecules Research (1 paper) and Biochemical and Structural Characterization (1 paper). The work is most often cited by research in Immunology and Allergy (106 citations), Molecular Biology (858 citations), Cellular and Molecular Neuroscience (113 citations), Biophysics (31 citations) and Sensory Systems (24 citations). Jack Schonbrun has collaborated with scholars based in United States. Frequent co-authors include David Baker, Vladimir Yarov‐Yarovoy, Patrick Barth, Dylan Chivian, William J. Wedemeyer, David E. Kim, Lars Malmström, Carol A. Rohl, Philip Bradley and Kira M.S. Misura. Their work appears in journals such as Proteins Structure Function and Bioinformatics, Proceedings of the National Academy of Sciences, Molecular Cell and Current Opinion in Structural 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.