Marc Robinson‐Rechavi
- Aging top 1%
- Genetics top 0.5%
- Genetic diversity and population structure 15
- Evolution and Genetic Dynamics 11
- Physiology top 1%
- Molecular Biology top 2%
- Genomics and Phylogenetic Studies 43
- RNA and protein synthesis mechanisms 17
- Bioinformatics and Genomic Networks 17
- Genomics and Chromatin Dynamics 13
- Gene expression and cancer classification 13
- Machine Learning in Bioinformatics 10
- Aquatic Science top 1%
- Co-authors
- Vincent LaudetHéctor EscriváNadezda Kryuchkova-MostacciDorothée HuchonRomain A. StuderJulien RouxFrédéric BrunetWalid H. Gharib
- Cited by
- AgingGeneticsPhysiology
- Journals
- Proceedings of the National Academy of Sciences (2 papers)Nucleic Acids Research (4 papers)Nature Communications (2 papers)
- Partner nations
- SwitzerlandFranceUnited States
In The Last Decade
Marc Robinson‐Rechavi
139 papers receiving 6.1k citations
Peers
Comparison fields: 5 of 164
- Aging 196
- Genetics 2.1k
- Physiology 285
- Molecular Biology 3.4k
- Aquatic Science 300
Countries citing papers authored by Marc Robinson‐Rechavi
This map shows the geographic impact of Marc Robinson‐Rechavi'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 Robinson‐Rechavi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marc Robinson‐Rechavi more than expected).
Fields of papers citing papers by Marc Robinson‐Rechavi
This network shows the impact of papers produced by Marc Robinson‐Rechavi. 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 Robinson‐Rechavi. The network helps show where Marc Robinson‐Rechavi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Marc Robinson‐Rechavi, 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 | 1 | |
| 2 | 2024 | 2 | |
| 3 | 2024 | 13 | |
| 4 | 2024 | 7 | |
| 5 | 2022 | 13 | |
| 6 | 2022 | 29 | |
| 7 | 2021 | 26 | |
| 8 | 2021 | 4 | |
| 9 | 2021 | 10 | |
| 10 | 2021 | 1 | |
| 11 | 2021 | 11 | |
| 12 | 2021 | 26 | |
| 13 | 2020 | 9 | |
| 14 | 2020 | 14 | |
| 15 | 2019 | 49 | |
| 16 | 2019 | 17 | |
| 17 | 2019 | 26 | |
| 18 | 2018 | 13 | |
| 19 | 2016 | 4 | |
| 20 | Targeting the Lunar Reconnaissance Orbiter Narrow Angle Cameras: Target Sources and Selection Strategy | 2009 | 2 |
About Marc Robinson‐Rechavi
Marc Robinson‐Rechavi is a scholar working on Aging, Genetics and Molecular Biology, having authored 143 papers that have together received 6.2k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (43 papers), RNA and protein synthesis mechanisms (17 papers), Bioinformatics and Genomic Networks (17 papers), Genetic diversity and population structure (15 papers), Genomics and Chromatin Dynamics (13 papers), Gene expression and cancer classification (13 papers), Evolution and Genetic Dynamics (11 papers) and Machine Learning in Bioinformatics (10 papers). The work is most often cited by research in Aging (196 citations), Genetics (2.1k citations) and Physiology (285 citations). Marc Robinson‐Rechavi has collaborated with scholars based in Switzerland, France and United States. Frequent co-authors include Vincent Laudet, Héctor Escrivá, Nadezda Kryuchkova-Mostacci, Dorothée Huchon, Romain A. Studer, Julien Roux, Frédéric Brunet, Walid H. Gharib, Adam Godzik and Christian Gautier. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.
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.