CORUM: the comprehensive resource of mammalian protein complexes—2019

By M. Giurgiu, Julian Reinhard, Barbara Brauner, I. Dunger, G. Fobo, Goar Frishman, Corinna Montrone, Andreas Ruepp. Nucleic Acids Res., 2018

580 citations recorded by the source corpus.

Abstract CORUM is a database that provides a manually curated repository of experimentally characterized protein complexes from mammalian organisms, mainly human (67%), mouse (15%) and rat (10%). Given the vital functions of these macromolecular machines, their identification and functional characterization is foundational to our understanding of normal and disease biology. The new CORUM 3.0 release encompasses 4274 protein complexes offering the largest and most comprehensive publicly available dataset of mammalian protein complexes. The CORUM dataset is built from 4473 different genes, representing 22% of the protein coding genes in humans. Protein complexes are described by a protein complex name, subunit composition, cellular functions as well as the literature references. Information about stoichiometry of subunits depends on availability of experimental data. Recent developments include a graphical tool displaying known interactions between subunits. This allows the prediction of structural interconnections within protein complexes of unknown structure. In addition, we present a set of 58 protein complexes with alternatively spliced subunits. Those were found to affect cellular functions such as regulation of apoptotic activity, protein complex assembly or define cellular localization. CORUM is freely accessible at http://mips.helmholtz-muenchen.de/corum/.

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/ff3ee33680ed8d30cc87501546551a592c07c38f

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Citations in the corpus

g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update) (2019, background): “This covers currently KEGG (19), Reactome (20) and WikiPathways (21); miRNA targets from miRTar-Base (22) and regulatory motif matches from TRANSFAC (23); tissue specificity based on expression data from Human Protein Atlas (24); protein complexes data from CO-RUM (25) and human disease phenotype as”
Building a knowledge graph to enable precision medicine (2022, methodology): “This resource integrates several protein-protein interaction databases, including TRANSFAC for regulatory interactions 82 , MINT and IntAct for yeast to hybrid binary interactions 83,84 , and CORUM for protein complex interactions 85 .”
Quantitative Proteomics of the Cancer Cell Line Encyclopedia (2020, unknown): “Protein Complex Relationship to Sensitivity and Mutation—Protein complex gene sets were taken from the CORUM database (Giurgiu et al., 2019).”
WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs (2019, background): “…subset of WikiPathways (7), co-expression network modules derived from cancer proteomics datasets from CPTAC (Clinical Proteomic Tumor Analysis Consortium), the protein complex database CORUM (8), the disease phenotype database OMIM (9), and kinase target genes compiled from PhosphoSitePlus (10).”
Dual Proteome-scale Networks Reveal Cell-specific Remodeling of the Human Interactome (2020, methodology): “Cell-line specificity varied with category (Figure 3E); those most closely associated with physical entities (e.g. CORUM, GO cellular components) overlapped more than abstract functional classes (e.g.”
OpenCell: proteome-scale endogenous tagging enables the cartography of human cellular organization (2022, methodology): “For recall analysis, we quantified the coverage in our data of interactions included in CORUM ( 30 ), a compendium of protein interactions manually curated fromthe literature.”
Towards a structurally resolved human protein interaction network (2021, methodology): “The average pDockQ score of CORUM is slightly higher than for hu.”
Comparative host-coronavirus protein interaction networks reveal pan-viral disease mechanisms. (2020, unknown): “For all proteins that fulfilled these criteria, we extracted information about the stable protein complexes that they participated in from the CORUM (46) database of known protein complexes.”
Scalable phylogenetic profiling using MinHash uncovers likely eukaryotic sexual reproduction genes (2019, methodology): “In that benchmark, the true positive protein-protein interactions (PPIs) were constructed using data available from CORUM [21] and the MIPS [22] databases for the human and yeast interaction datasets.”