Peter McQuilton

3.6k total citations · 1 hit paper
19 papers, 1.7k citations indexed

About

Peter McQuilton is a scholar working on Molecular Biology, Information Systems and Information Systems and Management. According to data from OpenAlex, Peter McQuilton has authored 19 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 6 papers in Information Systems and 5 papers in Information Systems and Management. Recurrent topics in Peter McQuilton's work include Biomedical Text Mining and Ontologies (7 papers), Research Data Management Practices (6 papers) and Genomics and Phylogenetic Studies (6 papers). Peter McQuilton is often cited by papers focused on Biomedical Text Mining and Ontologies (7 papers), Research Data Management Practices (6 papers) and Genomics and Phylogenetic Studies (6 papers). Peter McQuilton collaborates with scholars based in United Kingdom, United States and Germany. Peter McQuilton's co-authors include Susan E. St. Pierre, Jim Thurmond, Laura Ponting, Ray Stefancsik, Steven J Marygold, Gillian Millburn, Ruth L. Seal, Susan Tweedie, Kathleen Falls and David Osumi-Sutherland and has published in prestigious journals such as Nucleic Acids Research, PLoS Biology and BMC Bioinformatics.

In The Last Decade

Peter McQuilton

19 papers receiving 1.7k citations

Hit Papers

FlyBase: enhancing Drosophila Gene Ontology annotations 2008 2026 2014 2020 2008 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Peter McQuilton United Kingdom 13 1.1k 327 305 208 197 19 1.7k
Bert R. E. Klagges Germany 5 824 0.8× 698 2.1× 362 1.2× 46 0.2× 43 0.2× 6 1.5k
Maria Victoria Schneider United Kingdom 24 1.5k 1.4× 144 0.4× 682 2.2× 53 0.3× 92 0.5× 47 3.1k
David Osumi-Sutherland United Kingdom 15 954 0.9× 212 0.6× 254 0.8× 27 0.1× 22 0.1× 38 1.3k
Laura Elnitski United States 30 3.9k 3.6× 77 0.2× 1.2k 4.0× 82 0.4× 199 1.0× 75 5.0k
Mary Mangan United States 10 1.1k 1.0× 32 0.1× 247 0.8× 55 0.3× 127 0.6× 13 1.6k
Guruprasad Ananda United States 17 1.1k 1.1× 49 0.1× 354 1.2× 43 0.2× 112 0.6× 30 1.8k
Amelia Ireland United Kingdom 5 2.4k 2.2× 43 0.1× 360 1.2× 119 0.6× 145 0.7× 5 3.1k
Rachel Drysdale United Kingdom 13 1.1k 1.0× 444 1.4× 162 0.5× 23 0.1× 26 0.1× 16 1.4k
Steven J Marygold United Kingdom 16 1.6k 1.4× 406 1.2× 438 1.4× 21 0.1× 21 0.1× 32 2.2k
Petra Fey United States 19 1.0k 1.0× 54 0.2× 94 0.3× 88 0.4× 81 0.4× 40 1.9k

Countries citing papers authored by Peter McQuilton

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Peter McQuilton

This figure shows the co-authorship network connecting the top 25 collaborators of Peter McQuilton. A scholar is included among the top collaborators of Peter McQuilton based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Peter McQuilton. Peter McQuilton is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
Maxwell, Lauren, Delphine Dauga, Peter McQuilton, et al.. (2023). FAIR, ethical, and coordinated data sharing for COVID-19 response: a scoping review and cross-sectional survey of COVID-19 data sharing platforms and registries. The Lancet Digital Health. 5(10). e712–e736. 14 indexed citations
2.
Maxwell, Lauren, Delphine Dauga, Peter McQuilton, et al.. (2021). FAIR, ethical, and coordinated data sharing for COVID-19 response: a review of COVID-19 data sharing platforms and registries. Research Square. 2 indexed citations
3.
Wilkinson, Mark D., Michel Dumontier, Susanna‐Assunta Sansone, et al.. (2019). Evaluating FAIR maturity through a scalable, automated, community-governed framework. Scientific Data. 6(1). 174–174. 81 indexed citations
4.
Lamprecht, Anna‐Lena, Leyla García, Mateusz Kuzak, et al.. (2019). Towards FAIR principles for research software. Edinburgh Research Explorer. 3(1). 37–59. 150 indexed citations
5.
Sansone, Susanna‐Assunta, et al.. (2019). FAIRsharing Collaboration with DataCite and Publishers: Data Repository Selection, Criteria That Matter. OSF Preprints (OSF Preprints). 2 indexed citations
6.
Hettne, Kristina, Peter Wittenburg, Annika Jacobsen, et al.. (2019). FAIR Convergence Matrix: Optimizing the Reuse of Existing FAIR-Related Resources. Data Intelligence. 2(1-2). 158–170. 8 indexed citations
7.
McQuilton, Peter, Dominique Batista, Oya Beyan, et al.. (2019). Helping the Consumers and Producers of Standards, Repositories and Policies to Enable FAIR Data. Data Intelligence. 2(1-2). 151–157. 9 indexed citations
8.
McQuilton, Peter, Alejandra González-Beltrán, Philippe Rocca‐Serra, et al.. (2016). BioSharing: curated and crowd-sourced metadata standards, databases and data policies in the life sciences. Database. 2016. baw075–baw075. 46 indexed citations
9.
Cejuela, Juan Miguel, Peter McQuilton, Laura Ponting, et al.. (2014). tagtog: interactive and text-mining-assisted annotation of gene mentions in PLOS full-text articles. Database. 2014(0). bau033–bau033. 47 indexed citations
10.
Schaeffer, Mary, Peter McQuilton, Stanley J. F. Laulederkind, et al.. (2014). BC4GO: a full-text corpus for the BioCreative IV GO task. Database. 2014(0). bau074–bau074. 32 indexed citations
11.
Osumi-Sutherland, David, Steven J Marygold, Gillian Millburn, et al.. (2013). The Drosophila phenotype ontology. Journal of Biomedical Semantics. 4(1). 30–30. 16 indexed citations
12.
Pierre, Susan E. St., Laura Ponting, Ray Stefancsik, & Peter McQuilton. (2013). FlyBase 102—advanced approaches to interrogating FlyBase. Nucleic Acids Research. 42(D1). D780–D788. 241 indexed citations
13.
McQuilton, Peter. (2012). Opportunities for text mining in the FlyBase genetic literature curation workflow. Database. 2012(0). bas039–bas039. 7 indexed citations
14.
McQuilton, Peter, Susan E. St. Pierre, & Jim Thurmond. (2011). FlyBase 101 - the basics of navigating FlyBase. Nucleic Acids Research. 40(D1). D706–D714. 303 indexed citations
15.
McQuilton, Peter, et al.. (2009). Inside FlyBase: Biocuration as a career. Fly. 3(1). 112–114. 10 indexed citations
16.
Zhu, Bangfu, Peter McQuilton, Manuel G. Forero, et al.. (2008). Drosophila Neurotrophins Reveal a Common Mechanism for Nervous System Formation. PLoS Biology. 6(11). e284–e284. 92 indexed citations
17.
Karamanis, Nikiforos, Ruth L. Seal, Ian Lewin, et al.. (2008). Natural Language Processing in aid of FlyBase curators. BMC Bioinformatics. 9(1). 193–193. 31 indexed citations
18.
Tweedie, Susan, Michael Ashburner, Kathleen Falls, et al.. (2008). FlyBase: enhancing Drosophila Gene Ontology annotations. Nucleic Acids Research. 37(Database). D555–D559. 597 indexed citations breakdown →
19.
Hidalgo, Alicia, et al.. (2006). Neurotrophic and Gliatrophic Contexts in <i>Drosophila</i>. Brain Behavior and Evolution. 68(3). 173–180. 15 indexed citations

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.

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