Thomas Gaudelet
Impact in
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- Computational Drug Discovery Methods
Papers in
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- Bioinformatics and Genomic Networks 3
- Protein Structure and Dynamics 1
- Gene expression and cancer classification 1
- Chemical Synthesis and Analysis 1
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- Computational Drug Discovery Methods 2
- Co-authors
- Cristian Regep (2 shared papers)Noël Malod‐Dognin (2 shared papers)Michael M. Bronstein (2 shared papers)Jake P. Taylor‐King (2 shared papers)Jyothish Soman (1 shared paper)Tom L. Blundell (1 shared paper)David Roblin (1 shared paper)Nataša Pržulj (2 shared papers)
- Journals
- PLoS ONE (1 paper)Briefings in Bioinformatics (1 paper)Cell Reports Methods (1 paper)New Journal of Chemistry (1 paper)Bioinformatics (1 paper)
- Partner nations
- United KingdomCanadaUnited States
In The Last Decade
Thomas Gaudelet
5 papers receiving 232 citations
Peers
Comparison fields: 5 of 78
- Computational Theory and Mathematics 90
- Health Informatics 3
- Surfaces, Coatings and Films 14
- Biophysics 11
- Artificial Intelligence 58
Countries citing papers authored by Thomas Gaudelet
This map shows the geographic impact of Thomas Gaudelet'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 Thomas Gaudelet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Gaudelet more than expected).
Fields of papers citing papers by Thomas Gaudelet
This network shows the impact of papers produced by Thomas Gaudelet. 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 Thomas Gaudelet. The network helps show where Thomas Gaudelet may publish in the future.
Co-authors
The 25 scholars most cited alongside Thomas Gaudelet, 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 | 2021 | 162 | |
| 2 | 2018 | 30 | |
| 3 | 2016 | 24 | |
| 4 | 2020 | 13 | |
| 5 | 2023 | 9 |
About Thomas Gaudelet
Thomas Gaudelet is a scholar working on Molecular Biology, Computational Theory and Mathematics, Computational Mechanics, Surfaces, Coatings and Films and Biomedical Engineering, having authored 5 papers that have together received 238 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (3 papers), Computational Drug Discovery Methods (2 papers), Protein Structure and Dynamics (1 paper), Fluid Dynamics and Heat Transfer (1 paper), Gene expression and cancer classification (1 paper), Surface Modification and Superhydrophobicity (1 paper), Machine Learning in Materials Science (1 paper) and Chemical Synthesis and Analysis (1 paper). The work is most often cited by research in Computational Theory and Mathematics (90 citations), Health Informatics (3 citations), Surfaces, Coatings and Films (14 citations), Biophysics (11 citations) and Artificial Intelligence (58 citations). Thomas Gaudelet has collaborated with scholars based in United Kingdom, Canada and United States. Frequent co-authors include Cristian Regep, Noël Malod‐Dognin, Michael M. Bronstein, Jake P. Taylor‐King, Jyothish Soman, Tom L. Blundell, David Roblin, Nataša Pržulj, Arian R. Jamasb and Charles S. Roberts. Their work appears in journals such as PLoS ONE, Briefings in Bioinformatics, Cell Reports Methods, New Journal of Chemistry and Bioinformatics.
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.