Up-to-date catalogues of yeast protein complexes
By S. Pu, Jessica Wong, Brian Turner, Emerson Cho, Shoshana J. Wodak. Nucleic Acids Research, 2008
602 citations recorded by the source corpus.
Gold standard datasets on protein complexes are key to inferring and validating protein–protein interactions. Despite much progress in characterizing protein complexes in the yeast Saccharomyces cerevisiae, numerous researchers still use as reference the manually curated complexes catalogued by the Munich Information Center of Protein Sequences database. Although this catalogue has served the community extremely well, it no longer reflects the current state of knowledge. Here, we report two catalogues of yeast protein complexes as results of systematic curation efforts. The first one, denoted as CYC2008, is a comprehensive catalogue of 408 manually curated heteromeric protein complexes reliably backed by small-scale experiments reported in the current literature. This catalogue represents an up-to-date reference set for biologists interested in discovering protein interactions and protein complexes. The second catalogue, denoted as YHTP2008, comprises 400 high-throughput complexes annotated with current literature evidence. Among them, 262 correspond, at least partially, to CYC2008 complexes. Evidence for interacting subunits is collected for 68 complexes that have only partial or no overlap with CYC2008 complexes, whereas no literature evidence was found for 100 complexes. Some of these partially supported and as yet unsupported complexes may be interesting candidates for experimental follow up. Both catalogues are freely available at: http://wodaklab.org/cyc2008/.
Subfields: Molecular Biology
View Paper: https://www.semanticscholar.org/paper/bf2c0cc639d7bb59897b9dd33148478a21f999c2
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Citations in the corpus
- A proteome-wide fission yeast interactome reveals network evolution principles from yeasts to human (2016, background): “Using 408 high-quality literature-curated complexes from CYC2008 (Pu et al., 2009), we observed the same enrichment.”
- Learning Deep Representations for Graph Clustering (2014, methodology): “We used the protein complex data in CYC2008 (Pu et al. 2009) as the groundtruth for the two PPI networks.”