Peter Woollard

2.3k total citations
11 papers, 302 citations indexed

About

Peter Woollard is a scholar working on Molecular Biology, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Peter Woollard has authored 11 papers receiving a total of 302 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 4 papers in Artificial Intelligence and 2 papers in Computational Theory and Mathematics. Recurrent topics in Peter Woollard's work include Biomedical Text Mining and Ontologies (6 papers), Semantic Web and Ontologies (4 papers) and Bioinformatics and Genomic Networks (4 papers). Peter Woollard is often cited by papers focused on Biomedical Text Mining and Ontologies (6 papers), Semantic Web and Ontologies (4 papers) and Bioinformatics and Genomic Networks (4 papers). Peter Woollard collaborates with scholars based in United Kingdom, United States and Switzerland. Peter Woollard's co-authors include Anil Wipat, Simon Cockell, Debbie A. Smith, Stoyan Bardarov, Ruth A. McAdam, Selwyn Quan, Alan P. Lewis, Martin Everett, Jessica Vamathevan and Pauline T. Lukey and has published in prestigious journals such as PLoS ONE, Microbiology and Drug Discovery Today.

In The Last Decade

Peter Woollard

11 papers receiving 290 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peter Woollard United Kingdom 10 177 91 84 48 45 11 302
Mohd Zeeshan Ansari India 5 157 0.9× 137 1.5× 99 1.2× 58 1.2× 6 0.1× 16 386
Anna Lucarelli Italy 7 142 0.8× 141 1.5× 96 1.1× 13 0.3× 8 0.2× 18 256
Diogo F. T. Veiga United States 10 304 1.7× 195 2.1× 159 1.9× 29 0.6× 9 0.2× 22 500
Rethabile Khutlang South Africa 7 89 0.5× 151 1.7× 148 1.8× 18 0.4× 19 0.4× 11 428
Aditi Gupta United States 15 220 1.2× 171 1.9× 137 1.6× 45 0.9× 6 0.1× 31 656
S. S. Sheik India 7 205 1.2× 20 0.2× 18 0.2× 33 0.7× 56 1.2× 10 307
Nikolas Dovrolis Greece 13 232 1.3× 84 0.9× 56 0.7× 89 1.9× 15 0.3× 52 523
Rebecca Thomson United Kingdom 7 568 3.2× 42 0.5× 39 0.5× 41 0.9× 57 1.3× 10 729
Anne Gleizes Switzerland 9 581 3.3× 25 0.3× 59 0.7× 22 0.5× 23 0.5× 14 712

Countries citing papers authored by Peter Woollard

Since Specialization
Citations

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

Fields of papers citing papers by Peter Woollard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter Woollard

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

All Works

11 of 11 papers shown
1.
Harrow, Ian, Rama Balakrishnan, Ernesto Jiménez-Ruiz, et al.. (2019). Ontology mapping for semantically enabled applications. Drug Discovery Today. 24(10). 2068–2075. 34 indexed citations
2.
Harrow, Ian, Ernesto Jiménez-Ruiz, Andrea Splendiani, et al.. (2017). Matching disease and phenotype ontologies in the ontology alignment evaluation initiative. Journal of Biomedical Semantics. 8(1). 55–55. 20 indexed citations
3.
Cockell, Simon, et al.. (2016). An Integrated Data Driven Approach to Drug Repositioning Using Gene-Disease Associations. PLoS ONE. 11(5). e0155811–e0155811. 26 indexed citations
4.
Cockell, Simon, et al.. (2016). Mining integrated semantic networks for drug repositioning opportunities. PeerJ. 4. e1558–e1558. 15 indexed citations
5.
Vamathevan, Jessica, Matthew D. Hall, Samiul Hasan, et al.. (2013). Minipig and beagle animal model genomes aid species selection in pharmaceutical discovery and development. Toxicology and Applied Pharmacology. 270(2). 149–157. 40 indexed citations
6.
Rebholz‐Schuhmann, Dietrich, et al.. (2013). A case study: semantic integration of gene–disease associations for type 2 diabetes mellitus from literature and biomedical data resources. Drug Discovery Today. 19(7). 882–889. 9 indexed citations
7.
Harrow, Ian, Wendy Filsell, Peter Woollard, et al.. (2012). Towards Virtual Knowledge Broker services for semantic integration of life science literature and data sources. Drug Discovery Today. 18(9-10). 428–434. 10 indexed citations
8.
Woollard, Peter, Nalini Mehta, Jessica Vamathevan, et al.. (2011). The application of next-generation sequencing technologies to drug discovery and development. Drug Discovery Today. 16(11-12). 512–519. 31 indexed citations
9.
Woollard, Peter. (2010). Asking Complex Questions of the Genome Without Programming. Methods in molecular biology. 628. 39–52. 9 indexed citations
11.
Hillier, Keith, Patrick J. Roberts, & Peter Woollard. (1976). Catecholamine-stimulated prostaglandin synthesis in rat brain synaptosomes [proceedings].. PubMed. 58(3). 426P–427P. 2 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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