Helen Parkinson

37.7k total citations · 9 hit papers
113 papers, 9.1k citations indexed

About

Helen Parkinson is a scholar working on Molecular Biology, Genetics and Artificial Intelligence. According to data from OpenAlex, Helen Parkinson has authored 113 papers receiving a total of 9.1k indexed citations (citations by other indexed papers that have themselves been cited), including 82 papers in Molecular Biology, 26 papers in Genetics and 19 papers in Artificial Intelligence. Recurrent topics in Helen Parkinson's work include Biomedical Text Mining and Ontologies (54 papers), Bioinformatics and Genomic Networks (51 papers) and Gene expression and cancer classification (30 papers). Helen Parkinson is often cited by papers focused on Biomedical Text Mining and Ontologies (54 papers), Bioinformatics and Genomic Networks (51 papers) and Gene expression and cancer classification (30 papers). Helen Parkinson collaborates with scholars based in United Kingdom, United States and Russia. Helen Parkinson's co-authors include Tony Burdett, Jacqueline A. L. MacArthur, Paul Flicek, Lucia A. Hindorff, Danielle Welter, Peggy Hall, Heather Junkins, Joannella Morales, Alvis Brāzma and Teri A. Manolio and has published in prestigious journals such as Science, The Lancet and Nucleic Acids Research.

In The Last Decade

Helen Parkinson

107 papers receiving 8.9k citations

Hit Papers

The NHGRI GWAS Catalog, a... 2004 2026 2011 2018 2013 2016 2004 2006 2014 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Helen Parkinson United Kingdom 32 6.1k 2.8k 942 733 446 113 9.1k
Donna Maglott United States 26 7.6k 1.2× 3.8k 1.4× 1.7k 1.8× 342 0.5× 503 1.1× 48 11.5k
Suzanna Lewis United States 36 8.4k 1.4× 1.8k 0.6× 648 0.7× 1.7k 2.3× 467 1.0× 63 10.9k
Alvis Brāzma United Kingdom 50 11.0k 1.8× 1.6k 0.6× 1.4k 1.5× 670 0.9× 1.1k 2.4× 132 14.7k
Martin Hofmann‐Apitius Germany 51 5.3k 0.9× 922 0.3× 676 0.7× 936 1.3× 757 1.7× 290 11.6k
Peter N. Robinson Germany 59 7.3k 1.2× 5.5k 2.0× 1.6k 1.7× 922 1.3× 595 1.3× 326 13.4k
Jeffrey T. Chang United States 38 6.6k 1.1× 888 0.3× 1.6k 1.7× 384 0.5× 608 1.4× 109 9.5k
Vineet Bafna United States 54 7.5k 1.2× 2.8k 1.0× 1.4k 1.5× 674 0.9× 435 1.0× 199 10.4k
Kenneth H. Buetow United States 58 7.1k 1.2× 3.5k 1.3× 1.4k 1.5× 165 0.2× 758 1.7× 185 11.5k
Eivind Hovig Norway 46 6.0k 1.0× 1.1k 0.4× 2.3k 2.4× 384 0.5× 685 1.5× 218 8.9k
Michael Brudno Canada 39 6.3k 1.0× 2.3k 0.8× 913 1.0× 997 1.4× 249 0.6× 137 9.1k

Countries citing papers authored by Helen Parkinson

Since Specialization
Citations

This map shows the geographic impact of Helen Parkinson'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 Helen Parkinson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Helen Parkinson more than expected).

Fields of papers citing papers by Helen Parkinson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Helen Parkinson. 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 Helen Parkinson. The network helps show where Helen Parkinson may publish in the future.

Co-authorship network of co-authors of Helen Parkinson

This figure shows the co-authorship network connecting the top 25 collaborators of Helen Parkinson. A scholar is included among the top collaborators of Helen Parkinson 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 Helen Parkinson. Helen Parkinson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wilson, Robert, Min‐Yen Kan, Piia Keskivali-Bond, et al.. (2025). International Mouse Phenotyping Consortium Portal: facilitating investigation of gene function and providing insights into human disease. Nucleic Acids Research. 54(D1). D1133–D1142.
2.
McLaughlin, J. A., et al.. (2025). OLS4: a new Ontology Lookup Service for a growing interdisciplinary knowledge ecosystem. Bioinformatics. 41(5). 1 indexed citations
3.
Lambert, Samuel A., Joel T. Gibson, Laurent Gil, et al.. (2024). Enhancing the Polygenic Score Catalog with tools for score calculation and ancestry normalization. Nature Genetics. 56(10). 1989–1994. 14 indexed citations
4.
Perova, Zinaida, Federico López, Csaba Halmagyi, et al.. (2022). PDCM Finder: an open global research platform for patient-derived cancer models. Nucleic Acids Research. 51(D1). D1360–D1366. 8 indexed citations
5.
Pendlington, Zoë May, Paola Roncaglia, Julien Gobeill, et al.. (2022). COVoc and COVTriage: novel resources to support literature triage. Bioinformatics. 39(1). 1 indexed citations
6.
Cezard, Timothée, Fiona Cunningham, Sarah Hunt, et al.. (2021). The European Variation Archive: a FAIR resource of genomic variation for all species. Nucleic Acids Research. 50(D1). D1216–D1220. 62 indexed citations
7.
McMahon, Aoife, Elizabeth Lewis, Annalisa Buniello, et al.. (2021). Sequencing-based genome-wide association studies reporting standards. Cell Genomics. 1(1). 100005–100005. 10 indexed citations
8.
Lambert, Samuel A., Laurent Gil, Simon Jupp, et al.. (2021). The Polygenic Score Catalog as an open database for reproducibility and systematic evaluation. Nature Genetics. 53(4). 420–425. 320 indexed citations breakdown →
9.
Chapman, Martin, Shahzad Mumtaz, Luke V. Rasmussen, et al.. (2021). Desiderata for the development of next-generation electronic health record phenotype libraries. GigaScience. 10(9). 16 indexed citations
10.
Jupp, Simon, et al.. (2017). OxO - A Gravy of Ontology Mapping Extracts.. 4 indexed citations
11.
Sarntivijai, Sirarat, Drashtti Vasant, Simon Jupp, et al.. (2016). Linking rare and common disease: mapping clinical disease-phenotypes to ontologies in therapeutic target validation. Journal of Biomedical Semantics. 7(1). 8–8. 25 indexed citations
12.
Courtot, Mélanie, Alex Mitchell, Maxim Scheremetjew, et al.. (2016). Slim-o-matic: a Semi-Automated Way to Generate Gene Ontology Slims.. 1 indexed citations
13.
Montoliu, Lluı́s, Fabrizio Mammano, Yann Hérault, et al.. (2016). EMMA: The European Mouse Mutant Archive.. Transgenic Research. 25. 228. 1 indexed citations
14.
Jupp, Simon, Tony Burdett, Catherine Leroy, & Helen Parkinson. (2015). A new Ontology Lookup Service at EMBL-EBI.. 118–119. 45 indexed citations
15.
Jupp, Simon, Danielle Welter, Tony Burdett, Helen Parkinson, & James Malone. (2015). Collaborative Ontology Development Using the Webulous Architecture and Google App.. 120–121. 2 indexed citations
16.
Osumi-Sutherland, David, et al.. (2015). Cell, Chemical and Anatomical Views of the Gene Ontology: Mapping to a Roche Controlled Vocabulary.. 84–93. 2 indexed citations
17.
Adamusiak, Tomasz, Helen Parkinson, Juha Muilu, et al.. (2012). Observ-OM and Observ-TAB: Universal syntax solutions for the integration, search, and exchange of phenotype and genotype information. Human Mutation. 33(5). 867–873. 16 indexed citations
18.
Jupp, Simon, Helen Parkinson, & James Malone. (2012). Semantic Web Atlas: Putting Gene Expression Data into Biological Context.. 1 indexed citations
19.
Pang, Chao, Tomasz Adamusiak, Helen Parkinson, & James Malone. (2011). Rapid Development of an Ontology of Coriell Cell Lines..
20.
Swertz, Morris A., K. Joeri van der Velde, Bruno Tesson, et al.. (2010). XGAP: a uniform and extensible data model and software platform for genotype and phenotype experiments. Genome Biology. 11(3). R27–R27. 23 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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