Samuel Kerrien
Impact in
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- Bioinformatics and Genomic Networks
- Phosphodiesterase function and regulation
- Receptor Mechanisms and Signaling
- Biomedical Text Mining and Ontologies
- Metabolomics and Mass Spectrometry Studies
Papers in
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- Bioinformatics and Genomic Networks 6
- Biomedical Text Mining and Ontologies 4
- Microbial Metabolic Engineering and Bioproduction 2
- Gene expression and cancer classification 1
- Phosphodiesterase function and regulation 1
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- Advanced Proteomics Techniques and Applications 3
- Co-authors
- Henning Hermjakob (10 shared papers)Timothy P. Bonnert (1 shared paper)Nicholas J. Brandon (1 shared paper)Vincent Collura (1 shared paper)Kenji Mizuguchi (1 shared paper)Paul J. Whiting (1 shared paper)Luiz Miguel Camargo (1 shared paper)Philip Jones (2 shared papers)
- Journals
- PROTEOMICS (2 papers)BMC Bioinformatics (2 papers)Bioinformatics (2 papers)Database (1 paper)Genome biology (1 paper)
- Partner nations
- United KingdomFranceUnited States
In The Last Decade
Samuel Kerrien
12 papers receiving 623 citations
Peers
Comparison fields: 5 of 80
- Biological Psychiatry 24
- Molecular Biology 490
- Spectroscopy 90
- Cellular and Molecular Neuroscience 80
- Aging 7
Countries citing papers authored by Samuel Kerrien
This map shows the geographic impact of Samuel Kerrien'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 Samuel Kerrien with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Samuel Kerrien more than expected).
Fields of papers citing papers by Samuel Kerrien
This network shows the impact of papers produced by Samuel Kerrien. 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 Samuel Kerrien. The network helps show where Samuel Kerrien may publish in the future.
Co-authors
The 25 scholars most cited alongside Samuel Kerrien, 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 | 2006 | 334 | |
| 2 | 2007 | 101 | |
| 3 | 2007 | 47 | |
| 4 | 2009 | 42 | |
| 5 | 2008 | 32 | |
| 6 | 2021 | 30 | |
| 7 | 2008 | 19 | |
| 8 | 2009 | 16 | |
| 9 | 2013 | 9 | |
| 10 | 2007 | 5 | |
| 11 | 2008 | 3 | |
| 12 | 2006 | 1 |
About Samuel Kerrien
Samuel Kerrien is a scholar working on Molecular Biology, Spectroscopy, Computational Theory and Mathematics, Infectious Diseases and Pharmacology, having authored 12 papers that have together received 639 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (6 papers), Biomedical Text Mining and Ontologies (4 papers), Advanced Proteomics Techniques and Applications (3 papers), Computational Drug Discovery Methods (2 papers), Microbial Metabolic Engineering and Bioproduction (2 papers), SARS-CoV-2 detection and testing (1 paper), Gene expression and cancer classification (1 paper) and Phosphodiesterase function and regulation (1 paper). The work is most often cited by research in Biological Psychiatry (24 citations), Molecular Biology (490 citations), Spectroscopy (90 citations), Cellular and Molecular Neuroscience (80 citations) and Aging (7 citations). Samuel Kerrien has collaborated with scholars based in United Kingdom, France and United States. Frequent co-authors include Henning Hermjakob, Timothy P. Bonnert, Nicholas J. Brandon, Vincent Collura, Kenji Mizuguchi, Paul J. Whiting, Luiz Miguel Camargo, Philip Jones, Sandra Orchard and Florian Reisinger. Their work appears in journals such as PROTEOMICS, BMC Bioinformatics, Bioinformatics, Database and Genome biology.
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.