James Blackshaw
Impact in
- Genetics top 2%
- Genetic Associations and Epidemiology
- Rheumatology top 5%
- Folate and B Vitamins Research
Papers in
-
- Bioinformatics and Genomic Networks 2
- Metabolomics and Mass Spectrometry Studies 2
- Biomedical Text Mining and Ontologies 2
- Genetics 2
- Genetic Associations and Epidemiology 2
- Co-authors
- John Danesh (2 shared papers)Mihir Kamat (2 shared papers)Robin Young (2 shared papers)Adam S. Butterworth (2 shared papers)Stephen Burgess (2 shared papers)James R Staley (2 shared papers)Praveen Surendran (2 shared papers)Benjamin B. Sun (1 shared paper)
- Journals
- Bioinformatics (2 papers)Nucleic Acids Research (2 papers)SAE technical papers on CD-ROM/SAE technical paper series (1 paper)
- Partner nations
- United KingdomSwitzerlandGermany
In The Last Decade
James Blackshaw
5 papers receiving 2.7k citations
James Blackshaw's Hit Papers
Peers
Comparison fields: 5 of 134
- Genetics 1.0k
- Rheumatology 278
- Computational Theory and Mathematics 268
- Molecular Biology 957
- Gastroenterology 76
Countries citing papers authored by James Blackshaw
This map shows the geographic impact of James Blackshaw'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 James Blackshaw with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Blackshaw more than expected).
Fields of papers citing papers by James Blackshaw
This network shows the impact of papers produced by James Blackshaw. 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 James Blackshaw. The network helps show where James Blackshaw may publish in the future.
Co-authors
The 25 scholars most cited alongside James Blackshaw, 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 | PhenoScanner V2: an expanded tool for searching human genotype–phenotype associations Hit paper breakdown → | 2019 | 1269 |
| 2 | PhenoScanner: a database of human genotype–phenotype associations Hit paper breakdown → | 2016 | 883 |
| 3 | The ChEMBL Database in 2023: a drug discovery platform spanning multiple bioactivity data types and time periods Hit paper breakdown → | 2023 | 469 |
| 4 | 2011 | 73 | |
| 5 | 2014 | 2 |
About James Blackshaw
James Blackshaw is a scholar working on Molecular Biology, Genetics, Pharmacology, Computational Theory and Mathematics and Spectroscopy, having authored 5 papers that have together received 2.7k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (2 papers), Genetic Associations and Epidemiology (2 papers), Metabolomics and Mass Spectrometry Studies (2 papers), Biomedical Text Mining and Ontologies (2 papers), Computational Drug Discovery Methods (1 paper), Advanced Combustion Engine Technologies (1 paper), Microbial Natural Products and Biosynthesis (1 paper) and Biodiesel Production and Applications (1 paper). The work is most often cited by research in Genetics (1.0k citations), Rheumatology (278 citations), Computational Theory and Mathematics (268 citations), Molecular Biology (957 citations) and Gastroenterology (76 citations). James Blackshaw has collaborated with scholars based in United Kingdom, Switzerland and Germany. Frequent co-authors include John Danesh, Mihir Kamat, Robin Young, Adam S. Butterworth, Stephen Burgess, James R Staley, Praveen Surendran, Benjamin B. Sun, Ian O. Ellis and Dirk S. Paul. Their work appears in journals such as Bioinformatics, Nucleic Acids Research and SAE technical papers on CD-ROM/SAE technical paper series.
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.