Phil Bradley
Impact in
-
- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- Machine Learning in Bioinformatics
- Glycosylation and Glycoproteins Research
Papers in
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- RNA and protein synthesis mechanisms 4
- Genomics and Phylogenetic Studies 3
- Protein Structure and Dynamics 3
- Machine Learning in Bioinformatics 2
- Glycosylation and Glycoproteins Research 1
- Microbial Metabolic Engineering and Bioproduction 1
- Ecology 2
- Bacteriophages and microbial interactions 2
- Co-authors
- David Baker (2 shared papers)Kira M.S. Misura (1 shared paper)Ora Schueler‐Furman (1 shared paper)Chu Wang (1 shared paper)Ingemar André (1 shared paper)Andrew Leaver‐Fay (1 shared paper)Frank DiMaio (1 shared paper)Bonnie Berger (4 shared papers)
- Journals
- Nucleic Acids Research (1 paper)Journal of Computational Biology (1 paper)Proceedings of the National Academy of Sciences (1 paper)Science (1 paper)PLoS ONE (1 paper)
- Partner nations
- United StatesSouth AfricaIsrael
In The Last Decade
Phil Bradley
8 papers receiving 532 citations
Peers
Comparison fields: 5 of 84
- Structural Biology 10
- Molecular Biology 412
- Materials Chemistry 152
- Ecology 76
- Endocrinology 11
Countries citing papers authored by Phil Bradley
This map shows the geographic impact of Phil Bradley'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 Phil Bradley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Phil Bradley more than expected).
Fields of papers citing papers by Phil Bradley
This network shows the impact of papers produced by Phil Bradley. 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 Phil Bradley. The network helps show where Phil Bradley may publish in the future.
Co-authors
The 23 scholars most cited alongside Phil Bradley, 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 | 225 | |
| 2 | 2011 | 162 | |
| 3 | 2001 | 95 | |
| 4 | 2002 | 32 | |
| 5 | 2001 | 7 | |
| 6 | 2002 | 6 | |
| 7 | 2018 | 5 | |
| 8 | 2019 | 3 |
About Phil Bradley
Phil Bradley is a scholar working on Molecular Biology, Ecology, Materials Chemistry, Genetics and Immunology, having authored 8 papers that have together received 535 indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (4 papers), Genomics and Phylogenetic Studies (3 papers), Protein Structure and Dynamics (3 papers), Enzyme Structure and Function (2 papers), Bacteriophages and microbial interactions (2 papers), Machine Learning in Bioinformatics (2 papers), Glycosylation and Glycoproteins Research (1 paper) and Microbial Metabolic Engineering and Bioproduction (1 paper). The work is most often cited by research in Structural Biology (10 citations), Molecular Biology (412 citations), Materials Chemistry (152 citations), Ecology (76 citations) and Endocrinology (11 citations). Phil Bradley has collaborated with scholars based in United States, South Africa and Israel. Frequent co-authors include David Baker, Kira M.S. Misura, Ora Schueler‐Furman, Chu Wang, Ingemar André, Andrew Leaver‐Fay, Frank DiMaio, Bonnie Berger, Lenore Cowen and Matthew Menke. Their work appears in journals such as Nucleic Acids Research, Journal of Computational Biology, Proceedings of the National Academy of Sciences, Science and PLoS ONE.
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.