David Binns
Impact in
- Molecular Biology top 1%
- Genomics and Phylogenetic Studies
- Bioinformatics and Genomic Networks
- Machine Learning in Bioinformatics
- RNA and protein synthesis mechanisms
- Plant Science top 0.5%
- Plant-Microbe Interactions and Immunity
Papers in
-
- Bioinformatics and Genomic Networks 7
- Genomics and Phylogenetic Studies 7
- Biomedical Text Mining and Ontologies 5
- Machine Learning in Bioinformatics 3
- Microbial Metabolic Engineering and Bioproduction 2
- RNA and protein synthesis mechanisms 1
- Gene expression and cancer classification 1
-
- Advanced Proteomics Techniques and Applications 1
- Co-authors
- John MaslenRodrigo LópezSarah HunterCraig McAnullaSiew-Yit YongPhilip JonesGift NukaMaxim Scheremetjew
- Journals
- Bioinformatics (3 papers)Database (2 papers)Genome Research (1 paper)PROTEOMICS (1 paper)Nucleic Acids Research (1 paper)
- Partner nations
- United KingdomUnited States
In The Last Decade
David Binns
9 papers receiving 7.5k citations
Hit Papers
Peers
Comparison fields: 5 of 147
- Molecular Biology 4.6k
- Plant Science 2.2k
- Horticulture 49
- Ecology 1.3k
- Endocrinology 250
Countries citing papers authored by David Binns
This map shows the geographic impact of David Binns'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 David Binns with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Binns more than expected).
Fields of papers citing papers by David Binns
This network shows the impact of papers produced by David Binns. 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 David Binns. The network helps show where David Binns may publish in the future.
Co-authors
The 25 scholars most cited alongside David Binns, 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 | InterProScan 5: genome-scale protein function classification Hit paper breakdown → | 2014 | 5753 |
| 2 | 2011 | 6 | |
| 3 | QuickGO: a web-based tool for Gene Ontology searching Hit paper breakdown → | 2009 | 672 |
| 4 | 2009 | 46 | |
| 5 | 2008 | 452 | |
| 6 | 2008 | 34 | |
| 7 | 2005 | 142 | |
| 8 | 2004 | 133 | |
| 9 | 2003 | 273 |
About David Binns
David Binns is a scholar working on Molecular Biology, Spectroscopy, Infectious Diseases, Organic Chemistry and Surgery, having authored 9 papers that have together received 7.5k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (7 papers), Genomics and Phylogenetic Studies (7 papers), Biomedical Text Mining and Ontologies (5 papers), Machine Learning in Bioinformatics (3 papers), Microbial Metabolic Engineering and Bioproduction (2 papers), Advanced Proteomics Techniques and Applications (1 paper), RNA and protein synthesis mechanisms (1 paper) and Gene expression and cancer classification (1 paper). The work is most often cited by research in Molecular Biology (4.6k citations), Plant Science (2.2k citations), Horticulture (49 citations), Ecology (1.3k citations) and Endocrinology (250 citations). David Binns has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include John Maslen, Rodrigo López, Sarah Hunter, Craig McAnulla, Siew-Yit Yong, Philip Jones, Gift Nuka, Maxim Scheremetjew, Weizhong Li and Alex Mitchell. Their work appears in journals such as Bioinformatics, Database, Genome Research, PROTEOMICS and Nucleic Acids Research.
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.