Marc Vidal
Impact in
- Aging top 0.02%
- Genetics, Aging, and Longevity in Model Organisms
- Molecular Biology top 0.05%
- Bioinformatics and Genomic Networks
- Microbial Metabolic Engineering and Bioproduction
- Ubiquitin and proteasome pathways
- Gene Regulatory Network Analysis
- Mitochondrial Function and Pathology
Papers in
-
- Bioinformatics and Genomic Networks 72
- Fungal and yeast genetics research 32
- Microbial Metabolic Engineering and Bioproduction 28
- Genomics and Chromatin Dynamics 18
- RNA and protein synthesis mechanisms 18
- Genomics and Phylogenetic Studies 17
- CRISPR and Genetic Engineering 17
- Aging 34
- Genetics, Aging, and Longevity in Model Organisms 34
- Co-authors
- Michael E. Cusick (29 shared papers)Albert-László Barabási (9 shared papers)Albertha J.M. Walhout (20 shared papers)K.-I. Goh (2 shared papers)David E. Hill (59 shared papers)Barton Childs (1 shared paper)David Valle (1 shared paper)Tong Hao (20 shared papers)
- Journals
- Genome Research (18 papers)Proceedings of the National Academy of Sciences (12 papers)Nature Methods (12 papers)Molecular and Cellular Biology (9 papers)Cell (8 papers)
- Partner nations
- United StatesCanadaFrance
In The Last Decade
Marc Vidal
202 papers receiving 32.3k citations
Marc Vidal's Hit Papers
Peers
Comparison fields: 5 of 203
- Aging 2.9k
- Molecular Biology 24.6k
- Cell Biology 2.9k
- Computational Theory and Mathematics 3.0k
- Genetics 3.4k
Countries citing papers authored by Marc Vidal
This map shows the geographic impact of Marc Vidal'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 Vidal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marc Vidal more than expected).
Fields of papers citing papers by Marc Vidal
This network shows the impact of papers produced by Marc Vidal. 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 Vidal. The network helps show where Marc Vidal may publish in the future.
Co-authors
The 25 scholars most cited alongside Marc Vidal, 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 206 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | The human disease network Hit paper breakdown → | 2007 | 2497 |
| 2 | A Mitochondrial Protein Compendium Elucidates Complex I Disease Biology Hit paper breakdown → | 2008 | 1637 |
| 3 | Drug—target network Hit paper breakdown → | 2007 | 1415 |
| 4 | Evidence for dynamically organized modularity in the yeast protein–protein interaction network Hit paper breakdown → | 2004 | 1408 |
| 5 | Interactome Networks and Human Disease Hit paper breakdown → | 2011 | 1329 |
| 6 | Uncovering disease-disease relationships through the incomplete interactome Hit paper breakdown → | 2015 | 1076 |
| 7 | Toward Improving Caenorhabditis elegans Phenome Mapping With an ORFeome-Based RNAi Library Hit paper breakdown → | 2004 | 738 |
| 8 | A Protein–Protein Interaction Network for Human Inherited Ataxias and Disorders of Purkinje Cell Degeneration Hit paper breakdown → | 2006 | 619 |
| 9 | Protein Interaction Mapping in C. elegans Using Proteins Involved in Vulval Development Hit paper breakdown → | 2000 | 602 |
| 10 | A cDNA encoding a pRB-binding protein with properties of the transcription factor E2F Hit paper breakdown → | 1992 | 598 |
| 11 | [34] GATEWAY recombinational cloning: Application to the cloning of large numbers of open reading frames or ORFeomes Hit paper breakdown → | 2000 | 521 |
| 12 | Human papillomavirus 16 E6 oncoprotein binds to interferon regulatory factor-3 and inhibits its transcriptional activity Hit paper breakdown → | 1998 | 520 |
| 13 | 2001 | 486 | |
| 14 | 2006 | 480 | |
| 15 | 2012 | 456 | |
| 16 | A Systematic Screen for CDK4/6 Substrates Links FOXM1 Phosphorylation to Senescence Suppression in Cancer Cells Hit paper breakdown → | 2011 | 450 |
| 17 | 2014 | 439 | |
| 18 | 2004 | 437 | |
| 19 | 2003 | 423 | |
| 20 | Network-based in silico drug efficacy screening Hit paper breakdown → | 2016 | 416 |
About Marc Vidal
Marc Vidal is a scholar working on Molecular Biology, Aging, Genetics, Cell Biology and Oncology, having authored 206 papers that have together received 33.1k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (72 papers), Genetics, Aging, and Longevity in Model Organisms (34 papers), Fungal and yeast genetics research (32 papers), Microbial Metabolic Engineering and Bioproduction (28 papers), Genomics and Chromatin Dynamics (18 papers), RNA and protein synthesis mechanisms (18 papers), Genomics and Phylogenetic Studies (17 papers) and CRISPR and Genetic Engineering (17 papers). The work is most often cited by research in Aging (2.9k citations), Molecular Biology (24.6k citations), Cell Biology (2.9k citations), Computational Theory and Mathematics (3.0k citations) and Genetics (3.4k citations). Marc Vidal has collaborated with scholars based in United States, Canada and France. Frequent co-authors include Michael E. Cusick, Albert-László Barabási, Albertha J.M. Walhout, K.-I. Goh, David E. Hill, Barton Childs, David Valle, Tong Hao, Hui Ming Ge and Richard F. Gaber. Their work appears in journals such as Genome Research, Proceedings of the National Academy of Sciences, Nature Methods, Molecular and Cellular Biology and Cell.
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.