Marc Legeay
Impact in
- Cancer Research top 2%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
- Molecular Biology top 2%
- Bioinformatics and Genomic Networks
- RNA modifications and cancer
- Epigenetics and DNA Methylation
Papers in
-
- Advanced Proteomics Techniques and Applications 2
- Co-authors
- Rebecca KirschAnnika L. GableKaterina NastouSampo PyysaloNadezhda T. DonchevaChristian von MeringDamian SzklarczykTao Fang
- Journals
- Nucleic Acids Research (2 papers)Talanta (1 paper)BMC Systems Biology (1 paper)SHILAP Revista de lepidopterología (1 paper)HAL (Le Centre pour la Communication Scientifique Directe) (1 paper)
In The Last Decade
Marc Legeay
5 papers receiving 5.3k citations
Hit Papers
Peers
Comparison fields: 5 of 146
- Cancer Research 876
- Molecular Biology 3.3k
- Biological Psychiatry 90
- Pharmacology 290
- Immunology 592
Countries citing papers authored by Marc Legeay
This map shows the geographic impact of Marc Legeay'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 Marc Legeay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marc Legeay more than expected).
Fields of papers citing papers by Marc Legeay
This network shows the impact of papers produced by Marc Legeay. 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 Marc Legeay. The network helps show where Marc Legeay may publish in the future.
Co-authors
The 25 scholars most cited alongside Marc Legeay, 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 | 2025 | 0 | |
| 2 | 2021 | 2 | |
| 3 | Correction to ‘The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets’ Hit paper breakdown → | 2021 | 264 |
| 4 | The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets Hit paper breakdown → | 2020 | 5035 |
| 5 | 2018 | 1 | |
| 6 | 2016 | 1 |
About Marc Legeay
Marc Legeay is a scholar working on Spectroscopy, Biochemistry, Molecular Biology, Plant Science and Infectious Diseases, having authored 6 papers that have together received 5.3k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (3 papers), Advanced Proteomics Techniques and Applications (2 papers), Gene Regulatory Network Analysis (1 paper), Advanced Biosensing Techniques and Applications (1 paper), Metabolomics and Mass Spectrometry Studies (1 paper), Machine Learning in Bioinformatics (1 paper), Plant Pathogenic Bacteria Studies (1 paper) and Plant Gene Expression Analysis (1 paper). The work is most often cited by research in Cancer Research (876 citations), Molecular Biology (3.3k citations), Biological Psychiatry (90 citations), Pharmacology (290 citations) and Immunology (592 citations). Marc Legeay has collaborated with scholars based in France, Denmark and Germany. Frequent co-authors include Rebecca Kirsch, Annika L. Gable, Katerina Nastou, Sampo Pyysalo, Nadezhda T. Doncheva, Christian von Mering, Damian Szklarczyk, Tao Fang, David Lyon and Lars Juhl Jensen. Their work appears in journals such as Nucleic Acids Research, Talanta, BMC Systems Biology, SHILAP Revista de lepidopterología and HAL (Le Centre pour la Communication Scientifique Directe).
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.