Marc Vidal

64.2k total citations · 13 hit papers
199 papers, 31.0k citations indexed

About

Marc Vidal is a scholar working on Molecular Biology, Aging and Genetics. According to data from OpenAlex, Marc Vidal has authored 199 papers receiving a total of 31.0k indexed citations (citations by other indexed papers that have themselves been cited), including 166 papers in Molecular Biology, 35 papers in Aging and 25 papers in Genetics. Recurrent topics in Marc Vidal's work include Bioinformatics and Genomic Networks (67 papers), Genetics, Aging, and Longevity in Model Organisms (35 papers) and Fungal and yeast genetics research (31 papers). Marc Vidal is often cited by papers focused on Bioinformatics and Genomic Networks (67 papers), Genetics, Aging, and Longevity in Model Organisms (35 papers) and Fungal and yeast genetics research (31 papers). Marc Vidal collaborates with scholars based in United States, Canada and France. Marc Vidal's co-authors include Albert-Ĺaszló Barabási, Michael E. Cusick, Albertha J.M. Walhout, David E. Hill, K.-I. Goh, Barton Childs, David Valle, Tong Hao, Richard F. Gaber and Hui Ming Ge and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Marc Vidal

196 papers receiving 30.4k citations

Hit Papers

The human disease network 1992 2026 2003 2014 2007 2008 2007 2004 2011 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Marc Vidal United States 86 24.4k 3.5k 3.2k 3.0k 3.0k 199 31.0k
Stanley Fields United States 76 27.8k 1.1× 3.2k 0.9× 1.7k 0.5× 2.1k 0.7× 3.9k 1.3× 186 33.5k
Kara Dolinski United States 31 28.8k 1.2× 4.6k 1.3× 2.5k 0.8× 1.8k 0.6× 1.7k 0.6× 44 38.7k
Mike Tyers Canada 75 23.3k 1.0× 2.0k 0.6× 1.4k 0.4× 2.8k 0.9× 5.2k 1.8× 187 27.4k
David P. Hill United States 28 23.6k 1.0× 4.1k 1.2× 1.6k 0.5× 1.5k 0.5× 1.3k 0.5× 55 33.3k
Gavin Sherlock United States 52 35.0k 1.4× 6.3k 1.8× 1.9k 0.6× 2.7k 0.9× 2.2k 0.7× 127 49.1k
J. Michael Cherry United States 35 29.4k 1.2× 5.4k 1.5× 1.8k 0.6× 1.7k 0.6× 1.6k 0.5× 95 40.4k
Catherine A. Ball United States 29 25.2k 1.0× 4.6k 1.3× 1.6k 0.5× 1.7k 0.6× 1.5k 0.5× 48 35.3k
Gary D. Bader Canada 69 22.9k 0.9× 2.7k 0.8× 2.6k 0.8× 2.5k 0.8× 2.1k 0.7× 211 31.7k
Nevan J. Krogan United States 92 24.9k 1.0× 3.1k 0.9× 1.1k 0.3× 1.7k 0.6× 3.1k 1.1× 319 30.0k
Michael Ashburner United Kingdom 65 34.3k 1.4× 8.1k 2.3× 1.9k 0.6× 1.5k 0.5× 2.0k 0.7× 186 48.5k

Countries citing papers authored by Marc Vidal

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Marc Vidal

This figure shows the co-authorship network connecting the top 25 collaborators of Marc Vidal. A scholar is included among the top collaborators of Marc Vidal based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Marc Vidal. Marc Vidal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Vidal, Marc, et al.. (2025). The Time Machine: Future Scenario Generation Through Generative AI Tools. Future Internet. 17(1). 48–48. 2 indexed citations
2.
Urbanus, Malene L., Dayag Sheykhkarimli, Atina G. Coté, et al.. (2024). A comprehensive two-hybrid analysis to explore the Legionella pneumophila effector–effector interactome. mSystems. 9(12). e0100424–e0100424. 3 indexed citations
3.
Kumar, Ravinder, Sherry Flint-García, Marc Vidal, et al.. (2024). Optimization of Polyphenol Extraction from Purple Corn Pericarp Using Glycerol/Lactic Acid-Based Deep Eutectic Solvent in Combination with Ultrasound-Assisted Extraction. Antioxidants. 14(1). 9–9. 6 indexed citations
4.
Li, Zhaorong, Yilin Chen, Xing Liu, et al.. (2023). Paired yeast one-hybrid assays to detect DNA-binding cooperativity and antagonism across transcription factors. Nature Communications. 14(1). 4 indexed citations
5.
Sun, Song, Jochen Weile, Marta Verby, et al.. (2020). A proactive genotype-to-patient-phenotype map for cystathionine beta-synthase. Genome Medicine. 12(1). 13–13. 40 indexed citations
6.
Yang, Fan, Song Sun, Guihong Tan, et al.. (2017). Identifying pathogenicity of human variants via paralog-based yeast complementation. PLoS Genetics. 13(5). e1006779–e1006779. 24 indexed citations
7.
Chiu, Cindy N., Jason Rihel, Daniel A. Lee, et al.. (2016). A Zebrafish Genetic Screen Identifies Neuromedin U as a Regulator of Sleep/Wake States. Neuron. 89(4). 842–856. 62 indexed citations
8.
Sun, Song, Fan Yang, Guihong Tan, et al.. (2016). An extended set of yeast-based functional assays accurately identifies human disease mutations. Genome Research. 26(5). 670–680. 68 indexed citations
9.
Neupane, Manish, Allison Clark, Serena Landini, et al.. (2015). MECP2 Is a Frequently Amplified Oncogene with a Novel Epigenetic Mechanism That Mimics the Role of Activated RAS in Malignancy. Cancer Discovery. 6(1). 45–58. 49 indexed citations
10.
Wang, Yang, Nidhi Sahni, & Marc Vidal. (2015). Global Edgetic Rewiring in Cancer Networks. Cell Systems. 1(4). 251–253. 10 indexed citations
11.
Vidal, Marc. (2014). Interactome networks and human disease. ˜The œbiomedical & life sciences collection.. 2014(12). e1003858–e1003858. 1 indexed citations
12.
Dreze, Matija, Dario Monachello, Claire Lurin, et al.. (2010). High-Quality Binary Interactome Mapping. Methods in enzymology on CD-ROM/Methods in enzymology. 470. 281–315. 92 indexed citations
13.
Nicolo, Arcangela De, Emilio Parisini, Quan Zhong, et al.. (2009). Multimodal Assessment of Protein Functional Deficiency Supports Pathogenicity of BRCA1 p.V1688del. Cancer Research. 69(17). 7030–7037. 14 indexed citations
14.
Salehi‐Ashtiani, Kourosh, Chenwei Lin, Tong Hao, et al.. (2009). Large-scale RACE approach for proactive experimental definition of C. elegans ORFeome. Genome Research. 19(12). 2334–2342. 12 indexed citations
15.
Goh, K.-I., Michael E. Cusick, David Valle, et al.. (2007). The human disease network. Proceedings of the National Academy of Sciences. 104(21). 8685–8690. 2301 indexed citations breakdown →
16.
Temple, Gary, Philippe Lamesch, Stuart Milstein, et al.. (2006). From genome to proteome: developing expression clone resources for the human genome. Human Molecular Genetics. 15(suppl_1). R31–R43. 23 indexed citations
17.
Li, Ji, Muneesh Tewari, Marc Vidal, & Siu Sylvia Lee. (2006). The 14-3-3 protein FTT-2 regulates DAF-16 in Caenorhabditis elegans. Developmental Biology. 301(1). 82–91. 75 indexed citations
18.
Kim, John K., Harrison W. Gabel, Ravi S. Kamath, et al.. (2005). Functional Genomic Analysis of RNA Interference in C. elegans. Science. 308(5725). 1164–1167. 223 indexed citations
19.
Boulton, Simon J., Anton Gartner, Jérôme Reboul, et al.. (2002). Combined Functional Genomic Maps of the C. elegans DNA Damage Response. Science. 295(5552). 127–131. 229 indexed citations
20.
Vidal, Marc, et al.. (1990). Histamina y tiramina en derivados cárnicos. 30(1). 102–108. 6 indexed citations

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.

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