The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
High-Quality Binary Protein Interaction Map of the Yeast Interactome Network
Open accessAbstract
Current yeast interactome network maps contain several hundred molecular complexes with limited and somewhat controversial representation of direct binary interactions. We carried out a comparative quality assessment of current yeast interactome data sets, demonstrating that high-throughput yeast two-hybrid (Y2H) screening provides high-quality binary interaction information. Because a large fraction of the yeast binary interactome remains to be mapped, we developed an empirically controlled mapping framework to produce a “second-generation” high-quality, high-throughput Y2H data set covering ∼20% of all yeast binary interactions. Both Y2H and affinity purification followed by mass spectrometry (AP/MS) data are of equally high quality but of a fundamentally different and complementary nature, resulting in networks with different topological and biological properties. Compared to co-complex interactome models, this binary map is enriched for transient signaling interactions and intercomplex connections with a highly significant clustering between essential proteins. Rather than correlating with essentiality, protein connectivity correlates with genetic pleiotropy.
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“Several high-throughput experimental techniques have been designed to identify interacting protein partners23–26, but their results are far from complete and are often mutually inconsistent.”
From AF2Complex predicts direct physical interactions in multimeric proteins with deep learning (2022) · cites this paper as [26]
In the citing paper
“Yeast two hybrid (Y2H), affinity-purification mass spectrometry (APMS), and other high-throughput experimental approaches have identified many pairs of interacting proteins in yeast and other organisms (1–5), but there are discrepancies between sets generated using the different methods and considerable false positive and false negative rates (6–8).”
From Computed structures of core eukaryotic protein complexes (2021) · cites this paper as [5]
In the citing paper
“In a first set of calculations, we found that even with the advantages of S. cerevisiae and improved ortholog identification, the statistical method (Direct Coupling Analysis, DCA) we had used in our previous coevolution-guided protein-protein interaction (PPI) screen in Prokaryotes (9) (the more accurate GREMLIN (11) method is too slow for this) could not effectively distinguish a “gold standard””
From Computed structures of core eukaryotic protein complexes (2021) · cites this paper as [5]
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Metadata
- Authors
- Yu, H., Braun, P., Yıldırım, M. A., Lemmens, I., Venkatesan, K., Sahalie, J., Hirozane-Kishikawa, T., Gebreab, F., Li, N., Simonis, N., Hao, T., Rual, J.-F., Dricot, A., Vazquez, A., Murray, R. R., Simon, C., Tardivo, L., Tam, S., Svrzikapa, N., Fan, C., de Smet, A.-S., Motyl, A., Hudson, M. E., Park, J., Xin, X., Cusick, M. E., Moore, T., Boone, C., Snyder, M., Roth, F. P., Barabási, A.-L., Tavernier, J., Hill, D. E., & Vidal, M.
- Affiliations
- Harvard University (US)
- Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA 02115, USA.
- Northeastern University (US)
- Corresponding author
- Yu, Haiyuan
- Yıldırım, Muhammed A.
- Vidal, Marc
- ORCID
- Venue
- Science
- Published
- 2008-10-03
- Volume
- 322
- Issue
- 5898
- Pages
- 104-110
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC2746753
- OpenAlex
- W2109248504
- Cited by
- 1,392
- References
- 45
- Citations by year
- 2026: 18 · 2025: 26 · 2024: 29 · 2023: 34 · 2022: 63 · 2021: 55 · 2020: 66 · 2019: 65 · 2018: 67 · 2017: 72 · 2016: 68 · 2015: 78 · 2014: 79 · 2013: 122 · 2012: 172
- FWCI
- 51.78
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Ghent University Academic Bibliography (Ghent University) (submittedVersion)
- Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles) (submittedVersion, other-oa)
- Funders
- U.S. Public Health Service (U01A1070499-01)
- National Human Genome Research Institute (R01HG001715, R01HG003224, HG003224)
- National Cancer Institute (U56CA113004)
- National Institute of Allergy and Infectious Diseases (U01AI070499)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Keywords
- yeast interactome, protein-protein interaction network, yeast two-hybrid screening, affinity purification mass spectrometry, protein complexes, essential proteins, protein connectivity, pleiotropy, network topology
- MeSH terms
- Protein Binding, Saccharomyces cerevisiae, Mass Spectrometry, Transcription Factors, Signal Transduction, Computational Biology, Proteome, Two-Hybrid System Techniques, Protein Interaction Mapping, Saccharomyces cerevisiae Proteins, Protein Array Analysis, Proteomics, Gene Regulatory Networks, Metabolic Networks and Pathways
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