Didier Devaurs
Impact in
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- Computational Drug Discovery Methods
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- Robotic Path Planning Algorithms
Papers in
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- Protein Structure and Dynamics 13
- vaccines and immunoinformatics approaches 5
- RNA and protein synthesis mechanisms 3
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- Robotic Path Planning Algorithms 3
- Co-authors
- Dinler A. Antunes (15 shared papers)Lydia E. Kavraki (17 shared papers)Juan Cortés (6 shared papers)Thierry Siméon (6 shared papers)Mark Moll (9 shared papers)Gregory Lizée (5 shared papers)Robin Gras (2 shared papers)Maurício Rigo (4 shared papers)
- Journals
- Scientific Reports (2 papers)IEEE Transactions on Automation Science and Engineering (1 paper)Current Topics in Medicinal Chemistry (1 paper)Journal of Chemical Information and Modeling (1 paper)IEEE Transactions on NanoBioscience (1 paper)
- Partner nations
- United StatesFranceAustria
In The Last Decade
Didier Devaurs
29 papers receiving 720 citations
Peers
Comparison fields: 5 of 119
- Computational Theory and Mathematics 140
- Computer Vision and Pattern Recognition 156
- Molecular Biology 392
- Immunology 96
- Aerospace Engineering 92
Countries citing papers authored by Didier Devaurs
This map shows the geographic impact of Didier Devaurs'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 Didier Devaurs with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Didier Devaurs more than expected).
Fields of papers citing papers by Didier Devaurs
This network shows the impact of papers produced by Didier Devaurs. 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 Didier Devaurs. The network helps show where Didier Devaurs may publish in the future.
Co-authors
The 24 scholars most cited alongside Didier Devaurs, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 105 | |
| 2 | 2017 | 93 | |
| 3 | 2015 | 91 | |
| 4 | 2009 | 62 | |
| 5 | 2019 | 46 | |
| 6 | 2018 | 39 | |
| 7 | 2019 | 34 | |
| 8 | 2013 | 34 | |
| 9 | 2009 | 29 | |
| 10 | 2014 | 26 | |
| 11 | 2015 | 22 | |
| 12 | 2020 | 21 | |
| 13 | 2013 | 20 | |
| 14 | 2017 | 17 | |
| 15 | 2009 | 17 | |
| 16 | 2023 | 14 | |
| 17 | 2022 | 14 | |
| 18 | 2022 | 9 | |
| 19 | 2021 | 7 | |
| 20 | 2020 | 6 |
About Didier Devaurs
Didier Devaurs is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Spectroscopy and Immunology, having authored 29 papers that have together received 748 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (13 papers), Computational Drug Discovery Methods (5 papers), vaccines and immunoinformatics approaches (5 papers), Mass Spectrometry Techniques and Applications (4 papers), Personal Information Management and User Behavior (3 papers), Robotic Path Planning Algorithms (3 papers), RNA and protein synthesis mechanisms (3 papers) and Immunotherapy and Immune Responses (3 papers). The work is most often cited by research in Computational Theory and Mathematics (140 citations), Computer Vision and Pattern Recognition (156 citations), Molecular Biology (392 citations), Immunology (96 citations) and Aerospace Engineering (92 citations). Didier Devaurs has collaborated with scholars based in United States, France and Austria. Frequent co-authors include Dinler A. Antunes, Lydia E. Kavraki, Juan Cortés, Thierry Siméon, Mark Moll, Gregory Lizée, Robin Gras, Maurício Rigo, Stefanie Lindstaedt and Marc Vaisset. Their work appears in journals such as Scientific Reports, IEEE Transactions on Automation Science and Engineering, Current Topics in Medicinal Chemistry, Journal of Chemical Information and Modeling and IEEE Transactions on NanoBioscience.
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.