Philippe Sanséau
Impact in
- Computational Theory and Mathematics top 0.2%
- Computational Drug Discovery Methods
- Molecular Biology top 2%
- Bioinformatics and Genomic Networks
Papers in
-
- Computational Drug Discovery Methods 13
-
- Pharmacogenetics and Drug Metabolism 5
- Co-authors
- Christine J. McNameeMunir PirmohamedAlan NorrisSudeep PushpakomTim GuilliamsFrancesco IorioAndrew J. DoigShirley Hopper
- Journals
- Drug Discovery Today (11 papers)Scientific Reports (3 papers)BMC Evolutionary Biology (2 papers)Genomics (2 papers)Nature Reviews Drug Discovery (2 papers)
- Partner nations
- United KingdomUnited StatesFrance
In The Last Decade
Philippe Sanséau
46 papers receiving 5.4k citations
Hit Papers
Peers
Comparison fields: 5 of 163
- Computational Theory and Mathematics 1.3k
- Molecular Biology 3.0k
- Sensory Systems 176
- Infectious Diseases 576
- Pharmacology 248
Countries citing papers authored by Philippe Sanséau
This map shows the geographic impact of Philippe Sanséau'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 Philippe Sanséau with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philippe Sanséau more than expected).
Fields of papers citing papers by Philippe Sanséau
This network shows the impact of papers produced by Philippe Sanséau. 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 Philippe Sanséau. The network helps show where Philippe Sanséau may publish in the future.
Co-authors
The 25 scholars most cited alongside Philippe Sanséau, 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 | 2018 | 8 | |
| 2 | 2017 | 82 | |
| 3 | 2017 | 12 | |
| 4 | 2016 | 18 | |
| 5 | The support of human genetic evidence for approved drug indications Hit paper breakdown → | 2015 | 874 |
| 6 | 2014 | 53 | |
| 7 | 2013 | 280 | |
| 8 | 2013 | 40 | |
| 9 | 2012 | 18 | |
| 10 | 2011 | 34 | |
| 11 | 2011 | 32 | |
| 12 | 2011 | 11 | |
| 13 | 2005 | 90 | |
| 14 | 2004 | 92 | |
| 15 | 2002 | 10 | |
| 16 | 1996 | 66 | |
| 17 | ORGANIZATION AND FUNCTIONS OF THE CLASS-II REGION OF THE HUMAN MHC | 1994 | 1 |
| 18 | 1994 | 41 | |
| 19 | 1992 | 43 | |
| 20 | 1990 | 3 |
About Philippe Sanséau
Philippe Sanséau is a scholar working on Computational Theory and Mathematics, Pharmacology, Immunology, Molecular Biology and Genetics, having authored 46 papers that have together received 5.5k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (13 papers), Bioinformatics and Genomic Networks (7 papers), Pharmacogenetics and Drug Metabolism (5 papers), T-cell and B-cell Immunology (4 papers), Immune Cell Function and Interaction (4 papers), Genetics, Bioinformatics, and Biomedical Research (4 papers), Genomics and Chromatin Dynamics (4 papers) and Gene expression and cancer classification (4 papers). The work is most often cited by research in Computational Theory and Mathematics (1.3k citations), Molecular Biology (3.0k citations), Sensory Systems (176 citations), Infectious Diseases (576 citations) and Pharmacology (248 citations). Philippe Sanséau has collaborated with scholars based in United Kingdom, United States and France. Frequent co-authors include Christine J. McNamee, Munir Pirmohamed, Alan Norris, Sudeep Pushpakom, Tim Guilliams, Francesco Iorio, Andrew J. Doig, Shirley Hopper, David Cavalla and Patrick A. Eyers. Their work appears in journals such as Drug Discovery Today, Scientific Reports, BMC Evolutionary Biology, Genomics and Nature Reviews Drug Discovery.
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.