Raphaël A. G. Chaleil
- Molecular Biology top 10%
- Computational Theory and Mathematics top 2%
- Materials Chemistry
- Immunology
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Paul A. BatesIain H. MoalMieczyslaw TorchalaJuan Fernández‐RecioAnna VangonePanagiotis L. KastritisThom VrevenZhiping Weng
- Topics
- Protein Structure and Dynamics (10 papers)Microbial Metabolic Engineering and Bioproduction (5 papers)Computational Drug Discovery Methods (4 papers)
- Partner nations
- United KingdomSpainUnited States
In The Last Decade
Raphaël A. G. Chaleil
19 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 97
- Molecular Biology 757
- Computational Theory and Mathematics 247
- Materials Chemistry 188
- Immunology 183
- Radiology, Nuclear Medicine and Imaging 85
Countries citing papers authored by Raphaël A. G. Chaleil
This map shows the geographic impact of Raphaël A. G. Chaleil'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 Raphaël A. G. Chaleil with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raphaël A. G. Chaleil more than expected).
Fields of papers citing papers by Raphaël A. G. Chaleil
This network shows the impact of papers produced by Raphaël A. G. Chaleil. 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 Raphaël A. G. Chaleil. The network helps show where Raphaël A. G. Chaleil may publish in the future.
Co-authorship network of co-authors of Raphaël A. G. Chaleil
This figure shows the co-authorship network connecting the top 25 collaborators of Raphaël A. G. Chaleil. A scholar is included among the top collaborators of Raphaël A. G. Chaleil based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Raphaël A. G. Chaleil. Raphaël A. G. Chaleil is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 6 | |
| 3 | 3 | |
| 4 | 2 | |
| 5 | 15 | |
| 6 | 18 | |
| 7 | 167 | |
| 8 | 15 | |
| 9 | 1 | |
| 10 | 304 | |
| 11 | 66 | |
| 12 | 222 | |
| 13 | 30 | |
| 14 | 52 | |
| 15 | 8 | |
| 16 | 42 | |
| 17 | 3 | |
| 18 | Two-stage Bayesian networks for metabolic network prediction | 2 |
| 19 | 64 |
About Raphaël A. G. Chaleil
Raphaël A. G. Chaleil is a scholar working on Software, Molecular Biology and Computational Theory and Mathematics, having authored 19 papers that have together received 1.0k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (10 papers), Microbial Metabolic Engineering and Bioproduction (5 papers) and Computational Drug Discovery Methods (4 papers). The work is most often cited by research in Computational Theory and Mathematics (247 citations), Molecular Biology (757 citations) and Immunology (183 citations). Raphaël A. G. Chaleil has collaborated with scholars based in United Kingdom, Spain and United States. Frequent co-authors include Paul A. Bates, Iain H. Moal, Mieczyslaw Torchala, Juan Fernández‐Recio, Anna Vangone, Panagiotis L. Kastritis, Thom Vreven, Zhiping Weng, Alexandre M. J. J. Bonvin and Brian G. Pierce. Their work appears in journals such as Nature Immunology, Bioinformatics and Journal of Molecular 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.