Fantine Mordelet
Impact in
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- Bioinformatics and Genomic Networks
- Gene Regulatory Network Analysis
- Gene expression and cancer classification
- Machine Learning in Bioinformatics
- Genomics and Chromatin Dynamics
- Single-cell and spatial transcriptomics
- Artificial Intelligence top 10%
- Machine Learning and Data Classification
Papers in
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- Gene Regulatory Network Analysis 3
- RNA and protein synthesis mechanisms 2
- RNA Research and Splicing 2
- Gene expression and cancer classification 2
- Machine Learning in Bioinformatics 1
- Single-cell and spatial transcriptomics 1
- Co-authors
- Jean‐Philippe VertPaola Vera‐LiconaBarbara E. EngelhardtJ.R. HortonRaluca GordânAlexander J. HarteminkAthma A. PaiBianca Dumitrascu
- Journals
- Bioinformatics (2 papers)Pattern Recognition Letters (1 paper)BMC Systems Biology (1 paper)Nature Communications (1 paper)BMC Bioinformatics (1 paper)
- Partner nations
- FranceUnited States
In The Last Decade
Fantine Mordelet
7 papers receiving 789 citations
Peers
Comparison fields: 5 of 112
- Molecular Biology 560
- Artificial Intelligence 159
- Computational Theory and Mathematics 69
- Health Information Management 14
- Cancer Research 29
Countries citing papers authored by Fantine Mordelet
This map shows the geographic impact of Fantine Mordelet'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 Fantine Mordelet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fantine Mordelet more than expected).
Fields of papers citing papers by Fantine Mordelet
This network shows the impact of papers produced by Fantine Mordelet. 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 Fantine Mordelet. The network helps show where Fantine Mordelet may publish in the future.
Co-authorship network
The 9 scholars most cited alongside Fantine Mordelet, 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 | 2018 | 9 | |
| 2 | 2013 | 42 | |
| 3 | 2013 | 216 | |
| 4 | 2012 | 281 | |
| 5 | 2012 | 2 | |
| 6 | 2011 | 124 | |
| 7 | 2008 | 133 |
About Fantine Mordelet
Fantine Mordelet is a scholar working on Molecular Biology, Cancer Research, Genetics, Artificial Intelligence and Infectious Diseases, having authored 7 papers that have together received 807 indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (3 papers), RNA and protein synthesis mechanisms (2 papers), RNA Research and Splicing (2 papers), Gene expression and cancer classification (2 papers), Machine Learning in Bioinformatics (1 paper), Single-cell and spatial transcriptomics (1 paper), Bacterial Genetics and Biotechnology (1 paper) and Machine Learning and Algorithms (1 paper). The work is most often cited by research in Molecular Biology (560 citations), Artificial Intelligence (159 citations), Computational Theory and Mathematics (69 citations), Health Information Management (14 citations) and Cancer Research (29 citations). Fantine Mordelet has collaborated with scholars based in France and United States. Frequent co-authors include Jean‐Philippe Vert, Paola Vera‐Licona, Barbara E. Engelhardt, J.R. Horton, Raluca Gordân, Alexander J. Hartemink, Athma A. Pai, Bianca Dumitrascu and Derek Aguiar. Their work appears in journals such as Bioinformatics, Pattern Recognition Letters, BMC Systems Biology, Nature Communications 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.