Peter McQuilton
Impact in
- Aging top 5%
-
- Scientific Computing and Data Management
Papers in
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- Biomedical Text Mining and Ontologies 7
- Genomics and Phylogenetic Studies 5
- Bioinformatics and Genomic Networks 3
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- Research Data Management Practices 6
- Co-authors
- Susan E. St. Pierre (2 shared papers)Jim Thurmond (1 shared paper)Laura Ponting (3 shared papers)Ray Stefancsik (3 shared papers)Steven J Marygold (3 shared papers)Gillian Millburn (3 shared papers)Ruth L. Seal (2 shared papers)Kathleen Falls (2 shared papers)
- Journals
- Database (4 papers)Nucleic Acids Research (3 papers)Data Intelligence (2 papers)Fly (1 paper)BMC Bioinformatics (1 paper)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Peter McQuilton
20 papers receiving 1.7k citations
Peter McQuilton's Hit Papers
Peers
Comparison fields: 5 of 133
- Aging 69
- Information Systems and Management 175
- Cellular and Molecular Neuroscience 307
- Molecular Biology 975
- Genetics 272
Countries citing papers authored by Peter McQuilton
This map shows the geographic impact of Peter McQuilton'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 Peter McQuilton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter McQuilton more than expected).
Fields of papers citing papers by Peter McQuilton
This network shows the impact of papers produced by Peter McQuilton. 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 Peter McQuilton. The network helps show where Peter McQuilton may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter McQuilton, 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 | FlyBase: enhancing Drosophila Gene Ontology annotations Hit paper breakdown → | 2008 | 597 |
| 2 | 2011 | 303 | |
| 3 | 2013 | 242 | |
| 4 | 2019 | 159 | |
| 5 | 2008 | 92 | |
| 6 | 2019 | 82 | |
| 7 | 2014 | 47 | |
| 8 | 2016 | 46 | |
| 9 | 2014 | 32 | |
| 10 | 2008 | 31 | |
| 11 | 2023 | 16 | |
| 12 | 2013 | 16 | |
| 13 | 2006 | 15 | |
| 14 | 2009 | 11 | |
| 15 | 2019 | 10 | |
| 16 | 2019 | 8 | |
| 17 | 2012 | 7 | |
| 18 | 2019 | 2 | |
| 19 | 2021 | 2 | |
| 20 | 2021 | 1 |
About Peter McQuilton
Peter McQuilton is a scholar working on Molecular Biology, Information Systems, Information Systems and Management, Cellular and Molecular Neuroscience and Artificial Intelligence, having authored 20 papers that have together received 1.7k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (7 papers), Research Data Management Practices (6 papers), Scientific Computing and Data Management (5 papers), Genomics and Phylogenetic Studies (5 papers), Neurobiology and Insect Physiology Research (3 papers), Bioinformatics and Genomic Networks (3 papers), Semantic Web and Ontologies (3 papers) and Data Quality and Management (3 papers). The work is most often cited by research in Aging (69 citations), Information Systems and Management (175 citations), Cellular and Molecular Neuroscience (307 citations), Molecular Biology (975 citations) and Genetics (272 citations). Peter McQuilton has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Susan E. St. Pierre, Jim Thurmond, Laura Ponting, Ray Stefancsik, Steven J Marygold, Gillian Millburn, Ruth L. Seal, Kathleen Falls, Susan Tweedie and David Osumi-Sutherland. Their work appears in journals such as Database, Nucleic Acids Research, Data Intelligence, Fly and BMC 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.