Vincent Cabeli
Impact in
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- Cell Image Analysis Techniques
Papers in
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- Bioinformatics and Genomic Networks 2
- Genomics and Phylogenetic Studies 2
- Biomedical Text Mining and Ontologies 2
- Single-cell and spatial transcriptomics 1
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- Bayesian Modeling and Causal Inference 2
- Machine Learning in Healthcare 1
- Co-authors
- Mathieu Andreux (1 shared paper)Boris Muzellec (1 shared paper)Maria Teleńczuk (1 shared paper)Hervé Isambert (5 shared papers)Marc Verny (1 shared paper)Guido Uguzzoni (1 shared paper)Charles Durand (1 shared paper)Nathalie Chevallier (1 shared paper)
- Journals
- iScience (2 papers)eLife (1 paper)Bioinformatics (1 paper)npj Digital Medicine (1 paper)PLoS Computational Biology (1 paper)
- Partner nations
- FranceUnited StatesGermany
In The Last Decade
Vincent Cabeli
7 papers receiving 155 citations
Vincent Cabeli's Hit Papers
Peers
Comparison fields: 5 of 56
- Biophysics 15
- Developmental Neuroscience 5
- Aging 2
- Molecular Biology 71
- Neurology 7
Countries citing papers authored by Vincent Cabeli
This map shows the geographic impact of Vincent Cabeli'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 Vincent Cabeli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vincent Cabeli more than expected).
Fields of papers citing papers by Vincent Cabeli
This network shows the impact of papers produced by Vincent Cabeli. 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 Vincent Cabeli. The network helps show where Vincent Cabeli may publish in the future.
Co-authors
The 25 scholars most cited alongside Vincent Cabeli, 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 | PyDESeq2: a python package for bulk RNA-seq differential expression analysis Hit paper breakdown → | 2023 | 123 |
| 2 | 2020 | 12 | |
| 3 | 2020 | 9 | |
| 4 | 2024 | 5 | |
| 5 | 2022 | 5 | |
| 6 | 2024 | 2 | |
| 7 | 2024 | 2 | |
| 8 | 2026 | 0 |
About Vincent Cabeli
Vincent Cabeli is a scholar working on Molecular Biology, Artificial Intelligence, Cancer Research, Genetics and Oncology, having authored 8 papers that have together received 158 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (2 papers), Bioinformatics and Genomic Networks (2 papers), Genomics and Phylogenetic Studies (2 papers), Biomedical Text Mining and Ontologies (2 papers), Cancer-related molecular mechanisms research (2 papers), Machine Learning in Healthcare (1 paper), Hematopoietic Stem Cell Transplantation (1 paper) and Single-cell and spatial transcriptomics (1 paper). The work is most often cited by research in Biophysics (15 citations), Developmental Neuroscience (5 citations), Aging (2 citations), Molecular Biology (71 citations) and Neurology (7 citations). Vincent Cabeli has collaborated with scholars based in France, United States and Germany. Frequent co-authors include Mathieu Andreux, Boris Muzellec, Maria Teleńczuk, Hervé Isambert, Marc Verny, Guido Uguzzoni, Charles Durand, Nathalie Chevallier, Fabien Reyal and Pierre Charbord. Their work appears in journals such as iScience, eLife, Bioinformatics, npj Digital Medicine and PLoS Computational 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.