Jonathan C. Fuller
Impact in
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- Computational Drug Discovery Methods
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- Protein Structure and Dynamics
- Chemical Synthesis and Analysis
- RNA and protein synthesis mechanisms
- Protein Degradation and Inhibitors
Papers in ⓘ
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- Protein Structure and Dynamics 5
- Genetics, Bioinformatics, and Biomedical Research 2
- Bioinformatics and Genomic Networks 2
- Chemical Synthesis and Analysis 2
- Protein purification and stability 1
- Co-authors
- Rebecca C. Wade (4 shared papers)Richard M. Jackson (3 shared papers)Antonia Stank (2 shared papers)Daria B. Kokh (1 shared paper)Nicholas J. Burgoyne (1 shared paper)Michael R. Shirts (2 shared papers)Stefan Richter (2 shared papers)Andrew J. Wilson (1 shared paper)
- Journals
- PLoS ONE (2 papers)Accounts of Chemical Research (1 paper)PLoS Computational Biology (1 paper)Drug Discovery Today (1 paper)Bioinformatics (1 paper)
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
Jonathan C. Fuller
9 papers receiving 625 citations
Peers
Comparison fields: 5 of 97
- Computational Theory and Mathematics 197
- Molecular Biology 475
- Organic Chemistry 87
- Pharmacology 41
- Radiology, Nuclear Medicine and Imaging 54
Countries citing papers authored by Jonathan C. Fuller
This map shows the geographic impact of Jonathan C. Fuller'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 Jonathan C. Fuller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan C. Fuller more than expected).
Fields of papers citing papers by Jonathan C. Fuller
This network shows the impact of papers produced by Jonathan C. Fuller. 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 Jonathan C. Fuller. The network helps show where Jonathan C. Fuller may publish in the future.
Co-authors
The 25 scholars most cited alongside Jonathan C. Fuller, 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 | 2016 | 330 | |
| 2 | 2008 | 241 | |
| 3 | 2012 | 16 | |
| 4 | 2015 | 13 | |
| 5 | 2014 | 11 | |
| 6 | 2015 | 8 | |
| 7 | 2013 | 7 | |
| 8 | 2012 | 4 | |
| 9 | 2014 | 3 |
About Jonathan C. Fuller
Jonathan C. Fuller is a scholar working on Information Systems and Management, Molecular Biology, Computational Theory and Mathematics, Biomaterials and Cell Biology, having authored 9 papers that have together received 633 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (5 papers), Genetics, Bioinformatics, and Biomedical Research (2 papers), Computational Drug Discovery Methods (2 papers), Bioinformatics and Genomic Networks (2 papers), Enzyme Structure and Function (2 papers), Chemical Synthesis and Analysis (2 papers), Protein purification and stability (1 paper) and Cancer-related Molecular Pathways (1 paper). The work is most often cited by research in Computational Theory and Mathematics (197 citations), Molecular Biology (475 citations), Organic Chemistry (87 citations), Pharmacology (41 citations) and Radiology, Nuclear Medicine and Imaging (54 citations). Jonathan C. Fuller has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Rebecca C. Wade, Richard M. Jackson, Antonia Stank, Daria B. Kokh, Nicholas J. Burgoyne, Michael R. Shirts, Stefan Richter, Andrew J. Wilson, Thomas A. Edwards and Stefan Henrich. Their work appears in journals such as PLoS ONE, Accounts of Chemical Research, PLoS Computational Biology, Drug Discovery Today 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.