Bryan Lunt
Impact in
- Molecular Biology top 10%
- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- Genomics and Phylogenetic Studies
- Machine Learning in Bioinformatics
- Bioinformatics and Genomic Networks
- Microbial Metabolic Engineering and Bioproduction
- Genetics top 10%
- Evolution and Genetic Dynamics
Papers in
-
- Protein Structure and Dynamics 3
- RNA and protein synthesis mechanisms 3
- Bioinformatics and Genomic Networks 2
- Microbial Metabolic Engineering and Bioproduction 2
- DNA and Nucleic Acid Chemistry 1
- Genetics 3
- Bacterial Genetics and Biotechnology 3
- Co-authors
- Terence Hwa (4 shared papers)Martin Weigt (4 shared papers)Debora S. Marks (2 shared papers)Andrea Pagnani (1 shared paper)Riccardo Zecchina (2 shared papers)Chris Sander (2 shared papers)Faruck Morcos (2 shared papers)José N. Onuchic (2 shared papers)
- Journals
- Methods in enzymology on CD-ROM/Methods in enzymology (1 paper)Microbial Physiology (1 paper)Proceedings of the National Academy of Sciences (1 paper)Biophysical Journal (1 paper)Communications Biology (1 paper)
- Partner nations
- United StatesItalyFrance
In The Last Decade
Bryan Lunt
8 papers receiving 1.1k citations
Bryan Lunt's Hit Papers
Peers
Comparison fields: 5 of 78
- Molecular Biology 963
- Genetics 194
- Virology 25
- Computational Theory and Mathematics 72
- Materials Chemistry 194
Countries citing papers authored by Bryan Lunt
This map shows the geographic impact of Bryan Lunt'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 Bryan Lunt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bryan Lunt more than expected).
Fields of papers citing papers by Bryan Lunt
This network shows the impact of papers produced by Bryan Lunt. 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 Bryan Lunt. The network helps show where Bryan Lunt may publish in the future.
Co-authors
The 18 scholars most cited alongside Bryan Lunt, 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 | Direct-coupling analysis of residue coevolution captures native contacts across many protein families Hit paper breakdown → | 2011 | 1006 |
| 2 | 2011 | 70 | |
| 3 | 2010 | 36 | |
| 4 | 2014 | 9 | |
| 5 | 2012 | 2 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 1 | |
| 8 | 2020 | 1 | |
| 9 | 2024 | 0 |
About Bryan Lunt
Bryan Lunt is a scholar working on Molecular Biology, Genetics, Artificial Intelligence, Media Technology and Management Science and Operations Research, having authored 9 papers that have together received 1.1k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (3 papers), Bacterial Genetics and Biotechnology (3 papers), RNA and protein synthesis mechanisms (3 papers), Bioinformatics and Genomic Networks (2 papers), Microbial Metabolic Engineering and Bioproduction (2 papers), Construction Project Management and Performance (1 paper), Enzyme Structure and Function (1 paper) and DNA and Nucleic Acid Chemistry (1 paper). The work is most often cited by research in Molecular Biology (963 citations), Genetics (194 citations), Virology (25 citations), Computational Theory and Mathematics (72 citations) and Materials Chemistry (194 citations). Bryan Lunt has collaborated with scholars based in United States, Italy and France. Frequent co-authors include Terence Hwa, Martin Weigt, Debora S. Marks, Andrea Pagnani, Riccardo Zecchina, Chris Sander, Faruck Morcos, José N. Onuchic, Hendrik Szurmant and Andrea Procaccini. Their work appears in journals such as Methods in enzymology on CD-ROM/Methods in enzymology, Microbial Physiology, Proceedings of the National Academy of Sciences, Biophysical Journal and Communications 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.