Thierry Pécot
Impact in
- Biophysics top 5%
- Cell Image Analysis Techniques
- Cancer Research top 10%
- MicroRNA in disease regulation
Papers in
- Biophysics 20
- Cell Image Analysis Techniques 20
- Oncology 7
- Cancer-related Molecular Pathways 4
- Co-authors
- Gustavo W. Leone (12 shared papers)Raghu Machiraju (10 shared papers)Charles Kervrann A (14 shared papers)Kun Huang (7 shared papers)Jean Salamero (7 shared papers)Jérôme Boulanger A (7 shared papers)Michael C. Ostrowski (5 shared papers)Raleigh D. Kladney (3 shared papers)
- Journals
- Nature Cell Biology (3 papers)PLoS Computational Biology (2 papers)Journal of Computational Science (1 paper)IEEE Journal of Selected Topics in Signal Processing (1 paper)BMC Bioinformatics (1 paper)
- Partner nations
- FranceUnited StatesCanada
In The Last Decade
Thierry Pécot
43 papers receiving 976 citations
Peers
Comparison fields: 5 of 75
- Biophysics 94
- Cancer Research 165
- Oncology 205
- Cell Biology 73
- Hepatology 46
Countries citing papers authored by Thierry Pécot
This map shows the geographic impact of Thierry Pécot'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 Thierry Pécot with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thierry Pécot more than expected).
Fields of papers citing papers by Thierry Pécot
This network shows the impact of papers produced by Thierry Pécot. 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 Thierry Pécot. The network helps show where Thierry Pécot may publish in the future.
Co-authors
The 25 scholars most cited alongside Thierry Pécot, 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 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 239 | |
| 2 | 2012 | 133 | |
| 3 | 2012 | 88 | |
| 4 | 2015 | 56 | |
| 5 | 2019 | 50 | |
| 6 | 2015 | 48 | |
| 7 | 2013 | 40 | |
| 8 | 2013 | 32 | |
| 9 | 2023 | 26 | |
| 10 | 2014 | 25 | |
| 11 | 2023 | 24 | |
| 12 | 2023 | 20 | |
| 13 | 2022 | 19 | |
| 14 | 2018 | 17 | |
| 15 | 2015 | 13 | |
| 16 | 2019 | 13 | |
| 17 | 2021 | 13 | |
| 18 | 2021 | 12 | |
| 19 | 2023 | 12 | |
| 20 | 2011 | 11 |
About Thierry Pécot
Thierry Pécot is a scholar working on Biophysics, Oncology, Cell Biology, Media Technology and Cancer Research, having authored 48 papers that have together received 995 indexed citations. Recurring topics across this work include Cell Image Analysis Techniques (20 papers), AI in cancer detection (5 papers), Cancer-related Molecular Pathways (4 papers), Remote-Sensing Image Classification (3 papers), Microtubule and mitosis dynamics (2 papers), Immune cells in cancer (2 papers), Genomics and Chromatin Dynamics (2 papers) and Cellular Mechanics and Interactions (2 papers). The work is most often cited by research in Biophysics (94 citations), Cancer Research (165 citations), Oncology (205 citations), Cell Biology (73 citations) and Hepatology (46 citations). Thierry Pécot has collaborated with scholars based in France, United States and Canada. Frequent co-authors include Gustavo W. Leone, Raghu Machiraju, Charles Kervrann A, Kun Huang, Jean Salamero, Jérôme Boulanger A, Michael C. Ostrowski, Raleigh D. Kladney, Patrick Bouthémy and Zengzhen Liu. Their work appears in journals such as Nature Cell Biology, PLoS Computational Biology, Journal of Computational Science, IEEE Journal of Selected Topics in Signal Processing and BMC 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.