Marc Vidal
Impact in
- Molecular Biology top 0.02%
- Bioinformatics and Genomic Networks
- Protein Structure and Dynamics
- Genomics and Chromatin Dynamics
- Fungal and yeast genetics research
- Gene Regulatory Network Analysis
- Aging top 0.2%
Papers in
-
- Bioinformatics and Genomic Networks 103
- Fungal and yeast genetics research 23
- Genomics and Phylogenetic Studies 18
- Genomics and Chromatin Dynamics 14
- Developmental Biology and Gene Regulation 11
- Gene Regulatory Network Analysis 9
- Spectroscopy 16
- Advanced Proteomics Techniques and Applications 16
- Co-authors
- Michael E. Cusick (29 shared papers)Albert-László Barabási (8 shared papers)K. -I. Goh (2 shared papers)Albertha J.M. Walhout (19 shared papers)DAVID EDWIN HILL (47 shared papers)David Valle (1 shared paper)Barton Childs (1 shared paper)Muhammed Ali Yıldırım (6 shared papers)
- Journals
- Nature Methods (19 papers)Cell (14 papers)Proceedings of the National Academy of Sciences (14 papers)Nature (11 papers)Nature Communications (10 papers)
- Partner nations
- United StatesCanadaBelgium
In The Last Decade
Marc Vidal
246 papers receiving 48.3k citations
Marc Vidal's Hit Papers
Peers
Comparison fields: 5 of 202
- Molecular Biology 30.2k
- Aging 734
- Spectroscopy 2.7k
- Cell Biology 2.3k
- Computational Theory and Mathematics 2.5k
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 249 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | The human disease network Hit paper breakdown → | 2007 | 2562 |
| 2 | Towards a proteome-scale map of the human protein–protein interaction network Hit paper breakdown → | 2005 | 2360 |
| 3 | A Mitochondrial Protein Compendium Elucidates Complex I Disease Biology Hit paper breakdown → | 2008 | 1716 |
| 4 | Drug—target network Hit paper breakdown → | 2007 | 1439 |
| 5 | Evidence for dynamically organized modularity in the yeast protein–protein interaction network Hit paper breakdown → | 2004 | 1412 |
| 6 | Interactome Networks and Human Disease Hit paper breakdown → | 2011 | 1390 |
| 7 | A Map of the Interactome Network of the Metazoan C. elegans Hit paper breakdown → | 2004 | 1336 |
| 8 | COT drives resistance to RAF inhibition through MAP kinase pathway reactivation Hit paper breakdown → | 2010 | 1232 |
| 9 | Uncovering disease-disease relationships through the incomplete interactome Hit paper breakdown → | 2015 | 1166 |
| 10 | High-Quality Binary Protein Interaction Map of the Yeast Interactome Network Hit paper breakdown → | 2008 | 1133 |
| 11 | A Proteome-Scale Map of the Human Interactome Network Hit paper breakdown → | 2014 | 1067 |
| 12 | A reference map of the human binary protein interactome Hit paper breakdown → | 2020 | 827 |
| 13 | Evidence for Network Evolution in an Arabidopsis Interactome Map Hit paper breakdown → | 2011 | 777 |
| 14 | An empirical framework for binary interactome mapping Hit paper breakdown → | 2008 | 689 |
| 15 | Independently Evolved Virulence Effectors Converge onto Hubs in a Plant Immune System Network Hit paper breakdown → | 2011 | 685 |
| 16 | How many human proteoforms are there? Hit paper breakdown → | 2018 | 648 |
| 17 | A Protein–Protein Interaction Network for Human Inherited Ataxias and Disorders of Purkinje Cell Degeneration Hit paper breakdown → | 2006 | 642 |
| 18 | 2000 | 586 | |
| 19 | 1992 | 557 | |
| 20 | 2000 | 515 |
About Marc Vidal
Marc Vidal is a scholar working on Molecular Biology, Spectroscopy, Genetics, Cell Biology and Oncology, having authored 249 papers that have together received 49.5k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (103 papers), Fungal and yeast genetics research (23 papers), Genomics and Phylogenetic Studies (18 papers), Advanced Proteomics Techniques and Applications (16 papers), Genomics and Chromatin Dynamics (14 papers), Developmental Biology and Gene Regulation (11 papers), Cancer-related Molecular Pathways (10 papers) and Gene Regulatory Network Analysis (9 papers). The work is most often cited by research in Molecular Biology (30.2k citations), Aging (734 citations), Spectroscopy (2.7k citations), Cell Biology (2.3k citations) and Computational Theory and Mathematics (2.5k citations). Marc Vidal has collaborated with scholars based in United States, Canada and Belgium. Frequent co-authors include Michael E. Cusick, Albert-László Barabási, K. -I. Goh, Albertha J.M. Walhout, DAVID EDWIN HILL, David Valle, Barton Childs, Muhammed Ali Yıldırım, Jörg Menche and Tong Hao. Their work appears in journals such as Nature Methods, Cell, Proceedings of the National Academy of Sciences, Nature 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.