James Liley
Impact in
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- Computational Drug Discovery Methods
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- Vasculitis and related conditions
- Pulmonary Hypertension Research and Treatments
Papers in
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- Pulmonary Hypertension Research and Treatments 5
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- Artificial Intelligence in Healthcare and Education 2
- Co-authors
- Christopher Wallace (4 shared papers)Bilal Akhter Mateen (2 shared papers)Chris C. Holmes (2 shared papers)Alastair Keith Denniston (1 shared paper)Felix Ritchie (1 shared paper)Emmanuel Ogundimu (1 shared paper)Joanna Pepke‐Żaba (1 shared paper)Guy Dodgson (1 shared paper)
- Journals
- European Respiratory Journal (2 papers)Nature Communications (2 papers)American Journal of Respiratory and Critical Care Medicine (2 papers)BMC Bioinformatics (1 paper)PLoS Genetics (1 paper)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
James Liley
16 papers receiving 774 citations
James Liley's Hit Papers
Peers
Comparison fields: 5 of 78
- Computational Theory and Mathematics 178
- Pulmonary and Respiratory Medicine 307
- Health Informatics 19
- Genetics 82
- Modeling and Simulation 11
Countries citing papers authored by James Liley
This map shows the geographic impact of James Liley'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 Liley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Liley more than expected).
Fields of papers citing papers by James Liley
This network shows the impact of papers produced by James Liley. 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 Liley. The network helps show where James Liley may publish in the future.
Co-authors
The 25 scholars most cited alongside James Liley, 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 | Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen Hit paper breakdown → | 2019 | 263 |
| 2 | 2019 | 204 | |
| 3 | 2019 | 102 | |
| 4 | 2021 | 61 | |
| 5 | 2015 | 57 | |
| 6 | 2020 | 47 | |
| 7 | 2016 | 20 | |
| 8 | 2021 | 9 | |
| 9 | 2024 | 8 | |
| 10 | 2024 | 5 | |
| 11 | 2024 | 4 | |
| 12 | 2024 | 3 | |
| 13 | 2022 | 2 | |
| 14 | 2023 | 2 | |
| 15 | 2022 | 1 | |
| 16 | 2024 | 1 | |
| 17 | 2022 | 0 |
About James Liley
James Liley is a scholar working on Pulmonary and Respiratory Medicine, Health Informatics, Genetics, Health Information Management and Artificial Intelligence, having authored 17 papers that have together received 789 indexed citations. Recurring topics across this work include Pulmonary Hypertension Research and Treatments (5 papers), Genetic Associations and Epidemiology (4 papers), Artificial Intelligence in Healthcare and Education (2 papers), Privacy-Preserving Technologies in Data (2 papers), Artificial Intelligence in Healthcare (2 papers), Machine Learning in Healthcare (2 papers), Statistical Methods and Inference (1 paper) and Venous Thromboembolism Diagnosis and Management (1 paper). The work is most often cited by research in Computational Theory and Mathematics (178 citations), Pulmonary and Respiratory Medicine (307 citations), Health Informatics (19 citations), Genetics (82 citations) and Modeling and Simulation (11 citations). James Liley has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Christopher Wallace, Bilal Akhter Mateen, Chris C. Holmes, Alastair Keith Denniston, Felix Ritchie, Emmanuel Ogundimu, Joanna Pepke‐Żaba, Guy Dodgson, Ben Alderson‐Day and Charles Fernyhough. Their work appears in journals such as European Respiratory Journal, Nature Communications, American Journal of Respiratory and Critical Care Medicine, BMC Bioinformatics and PLoS Genetics.
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.