ArticleMolecular & cellular proteomics : MCP2009
A complex-based reconstruction of the Saccharomyces cerevisiae interactome.
Article in Molecular & cellular proteomics : MCP, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
- An application of node and edge nonlinear hypergraph centrality to a protein complex hypernetwork.PloS one · 2024Article
- Article
- Assembling Disease Networks From Causal Interaction Resources.Frontiers in genetics · 2021Review
- Protein Complexes Form a Basis for Complex Hybrid Incompatibility.Frontiers in genetics · 2021Review
- Identifying protein complexes based on an edge weight algorithm and core-attachment structure.BMC bioinformatics · 2019Article
- Link clustering explains non-central and contextually essential genes in protein interaction networks.Scientific reports · 2019Article
- Protein complexes identification based on go attributed network embedding.BMC bioinformatics · 2018Article
- Network biology discovers pathogen contact points in host protein-protein interactomes.Nature communications · 2018Article
- Emerging and evolving concepts in gene essentiality.Nature reviews. Genetics · 2018Review
- Protein complex finding and ranking: An application to Alzheimer's disease.Journal of biosciences · 2017Article
- Integration of over 9,000 mass spectrometry experiments builds a global map of human protein complexes.Molecular systems biology · 2017Article
- Systematic Analyses and Prediction of Human Drug Side Effect Associated Proteins from the Perspective of Protein Evolution.Genome biology and evolution · 2017Article
- Protein complex prediction for large protein protein interaction networks with the Core&Peel method.BMC bioinformatics · 2016Article
- Graph theory and stability analysis of protein complex interaction networks.IET systems biology · 2016Article
- Fundamentals of protein interaction network mapping.Molecular systems biology · 2015Review
- Identification of Essential Proteins Based on a New Combination of Local Interaction Density and Protein Complexes.PloS one · 2015Article
- Reconstructing genome-wide protein-protein interaction networks using multiple strategies with homologous mapping.PloS one · 2015Article
- Increasing the precision of orthology-based complex prediction through network alignment.PeerJ · 2014Article
- Predicting physical interactions between protein complexes.Molecular & cellular proteomics : MCP · 2013Article
- Cell type-specific nuclear pores: a case in point for context-dependent stoichiometry of molecular machines.Molecular systems biology · 2013Article
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Authors and funding
10 authors.
Funding
Abstract
Most cellular processes are performed by proteomic units that interact with each other. These units are often stoichiometrically stable complexes comprised of several proteins. To obtain a faithful view of the protein interactome we must view it in terms of these basic units (complexes and proteins) and the interactions between them. This study makes two contributions toward this goal. First, it provides a new algorithm for reconstruction of stable complexes from a variety of heterogeneous biological assays; our approach combines state-of-the-art machine learning methods with a novel hierarchical clustering algorithm that allows clusters to overlap. We demonstrate that our approach constructs over 40% more known complexes than other recent methods and that the complexes it produces are more biologically coherent even compared with the reference set. We provide experimental support for some of our novel predictions, identifying both a new complex involved in nutrient starvation and a new component of the eisosome complex. Second, we provide a high accuracy algorithm for the novel problem of predicting transient interactions involving complexes. We show that our complex level network, which we call ComplexNet, provides novel insights regarding the protein-protein interaction network. In particular, we reinterpret the finding that "hubs" in the network are enriched for being essential, showing instead that essential proteins tend to be clustered together in essential complexes and that these essential complexes tend to be large.
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