Manon Réau
Impact in
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- Computational Drug Discovery Methods
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- Protein Structure and Dynamics
- Machine Learning in Bioinformatics
- Bioinformatics and Genomic Networks
- RNA and protein synthesis mechanisms
Papers in
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- Computational Drug Discovery Methods 9
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- Protein Structure and Dynamics 5
- Receptor Mechanisms and Signaling 2
- Bioinformatics and Genomic Networks 1
- Co-authors
- Alexandre M. J. J. Bonvin (4 shared papers)Nicolas Renaud (2 shared papers)Li C. Xue (2 shared papers)Matthieu Montès (6 shared papers)Jean‐François Zagury (5 shared papers)Nathalie Lagarde (5 shared papers)Cunliang Geng (2 shared papers)Sonja Georgievska (1 shared paper)
- Journals
- Frontiers in Endocrinology (1 paper)Cells (1 paper)Nature Communications (1 paper)Proteins Structure Function and Bioinformatics (1 paper)Journal of Medicinal Chemistry (1 paper)
- Partner nations
- FranceNetherlandsSwitzerland
In The Last Decade
Manon Réau
11 papers receiving 311 citations
Peers
Comparison fields: 5 of 82
- Computational Theory and Mathematics 163
- Molecular Biology 209
- Biophysics 11
- Materials Chemistry 69
- Pharmacology 23
Countries citing papers authored by Manon Réau
This map shows the geographic impact of Manon Réau'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 Manon Réau with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manon Réau more than expected).
Fields of papers citing papers by Manon Réau
This network shows the impact of papers produced by Manon Réau. 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 Manon Réau. The network helps show where Manon Réau may publish in the future.
Co-authors
The 25 scholars most cited alongside Manon Réau, 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 | 2022 | 97 | |
| 2 | 2018 | 79 | |
| 3 | 2021 | 76 | |
| 4 | 2018 | 18 | |
| 5 | 2017 | 12 | |
| 6 | 2021 | 12 | |
| 7 | 2022 | 7 | |
| 8 | 2019 | 7 | |
| 9 | 2017 | 6 | |
| 10 | 2019 | 3 | |
| 11 | 2024 | 1 |
About Manon Réau
Manon Réau is a scholar working on Computational Theory and Mathematics, Molecular Biology, Pharmacology, Pharmacology and Genetics, having authored 11 papers that have together received 318 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (9 papers), Protein Structure and Dynamics (5 papers), Estrogen and related hormone effects (3 papers), Pharmacogenetics and Drug Metabolism (3 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Receptor Mechanisms and Signaling (2 papers), Microbial Natural Products and Biosynthesis (2 papers) and Bioinformatics and Genomic Networks (1 paper). The work is most often cited by research in Computational Theory and Mathematics (163 citations), Molecular Biology (209 citations), Biophysics (11 citations), Materials Chemistry (69 citations) and Pharmacology (23 citations). Manon Réau has collaborated with scholars based in France, Netherlands and Switzerland. Frequent co-authors include Alexandre M. J. J. Bonvin, Nicolas Renaud, Li C. Xue, Matthieu Montès, Jean‐François Zagury, Nathalie Lagarde, Cunliang Geng, Sonja Georgievska, Francesco Ambrosetti and Lars Ridder. Their work appears in journals such as Frontiers in Endocrinology, Cells, Nature Communications, Proteins Structure Function and Bioinformatics and Journal of Medicinal Chemistry.
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.