Arnaud Céol
- Molecular Biology top 5%
- Bioinformatics and Genomic Networks 19
- Microbial Metabolic Engineering and Bioproduction 8
- Biomedical Text Mining and Ontologies 7
- Protein Structure and Dynamics 5
- Genomics and Phylogenetic Studies 5
- Machine Learning in Bioinformatics 2
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- Computational Drug Discovery Methods 3
- Spectroscopy top 5%
- Cell Biology top 10%
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- Microbial Natural Products and Biosynthesis 3
- Co-authors
- Gianni CesareniPatrick AloyLuisa CastagnoliRoberto MoscaAndrew Chatr‐aryamontriMaria Victoria SchneiderGiovanni Battista NardelliAmelie Stein
- Partner nations
- ItalySpainUnited States
In The Last Decade
Arnaud Céol
30 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 115
- Molecular Biology 2.5k
- Computational Theory and Mathematics 539
- Spectroscopy 186
- Cell Biology 134
- Aging 13
Countries citing papers authored by Arnaud Céol
This map shows the geographic impact of Arnaud Céol'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 Arnaud Céol with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arnaud Céol more than expected).
Fields of papers citing papers by Arnaud Céol
This network shows the impact of papers produced by Arnaud Céol. 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 Arnaud Céol. The network helps show where Arnaud Céol may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Arnaud Céol, 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 | 2024 | 2 | |
| 2 | 2021 | 1 | |
| 3 | 2020 | 5 | |
| 4 | 2016 | 35 | |
| 5 | 2016 | 14 | |
| 6 | 2014 | 43 | |
| 7 | 2014 | 172 | |
| 8 | 2014 | 29 | |
| 9 | 2013 | 77 | |
| 10 | 2013 | 185 | |
| 11 | 2012 | 28 | |
| 12 | 2010 | 109 | |
| 13 | 2010 | 38 | |
| 14 | 2009 | 394 | |
| 15 | 2008 | 155 | |
| 16 | 2008 | 45 | |
| 17 | 2006 | 63 | |
| 18 | MINT: the Molecular INTeraction databasebreakdown → | 2006 | 759 |
| 19 | 2005 | 105 | |
| 20 | 2005 | 35 |
About Arnaud Céol
Arnaud Céol is a scholar working on Molecular Biology, Endocrinology, Computational Theory and Mathematics, Pharmacology and Biophysics, having authored 30 papers that have together received 2.7k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (19 papers), Microbial Metabolic Engineering and Bioproduction (8 papers), Biomedical Text Mining and Ontologies (7 papers), Protein Structure and Dynamics (5 papers), Genomics and Phylogenetic Studies (5 papers), Microbial Natural Products and Biosynthesis (3 papers), Computational Drug Discovery Methods (3 papers) and Machine Learning in Bioinformatics (2 papers). The work is most often cited by research in Molecular Biology (2.5k citations), Computational Theory and Mathematics (539 citations), Spectroscopy (186 citations), Cell Biology (134 citations) and Aging (13 citations). Arnaud Céol has collaborated with scholars based in Italy, Spain and United States. Frequent co-authors include Gianni Cesareni, Patrick Aloy, Luisa Castagnoli, Roberto Mosca, Andrew Chatr‐aryamontri, Maria Victoria Schneider, Giovanni Battista Nardelli, Amelie Stein, Luana Licata and Daniele Peluso. Their work appears in journals such as Nucleic Acids Research, BMC Bioinformatics, FEBS Letters, Bioinformatics and Nature Methods.
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.