ArticleMolecular & cellular proteomics : MCP2011
Large-scale de novo prediction of physical protein-protein association.
Article in Molecular & cellular proteomics : MCP, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- DriverOmicsNet: an integrated graph convolutional network for multi-omics exploration of cancer driver genes.Briefings in bioinformatics · 2025Article
- Network assisted analysis of de novo variants using protein-protein interaction information identified 46 candidate genes for congenital heart disease.PLoS genetics · 2022Article
- JAK-STAT core cancer pathway: An integrative cancer interactome analysis.Journal of cellular and molecular medicine · 2022Review
- IID 2021: towards context-specific protein interaction analyses by increased coverage, enhanced annotation and enrichment analysis.Nucleic acids research · 2022Article
- Genome-wide functional association networks: background, data & state-of-the-art resources.Briefings in bioinformatics · 2020Review
- Protein-Protein Interactions Efficiently Modeled by Residue Cluster Classes.International journal of molecular sciences · 2020Article
- Identification of Candidate Genes Associated with Charcot-Marie-Tooth Disease by Network and Pathway Analysis.BioMed research international · 2020Article
- A Computational Framework for Predicting Direct Contacts and Substructures within Protein Complexes.Biomolecules · 2019Article
- IID 2018 update: context-specific physical protein-protein interactions in human, model organisms and domesticated species.Nucleic acids research · 2019Article
- Combination of novel and public RNA-seq datasets to generate an mRNA expression atlas for the domestic chicken.BMC genomics · 2018Article
- A computational framework for distinguishing direct versus indirect interactions in human functional protein-protein interaction networks.Integrative biology : quantitative biosciences from nano to macro · 2017Article
- Proteomics Analysis with a Nano Random Forest Approach Reveals Novel Functional Interactions Regulated by SMC Complexes on Mitotic Chromosomes.Molecular & cellular proteomics : MCP · 2016Article
- Integrated interactions database: tissue-specific view of the human and model organism interactomes.Nucleic acids research · 2016Article
- Fundamentals of protein interaction network mapping.Molecular systems biology · 2015Review
- Efficient prediction of progesterone receptor interactome using a support vector machine model.International journal of molecular sciences · 2015Article
- Forward Individualized Medicine from Personal Genomes to Interactomes.Frontiers in physiology · 2015Review
- In silico prediction of physical protein interactions and characterization of interactome orphans.Nature methods · 2015Article
- Efficient prediction of human protein-protein interactions at a global scale.BMC bioinformatics · 2014Article
- Genomics meets proteomics: identifying the culprits in disease.Human genetics · 2014Review
- FunCoup 3.0: database of genome-wide functional coupling networks.Nucleic acids research · 2014Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Information about the physical association of proteins is extensively used for studying cellular processes and disease mechanisms. However, complete experimental mapping of the human interactome will remain prohibitively difficult in the near future. Here we present a map of predicted human protein interactions that distinguishes functional association from physical binding. Our network classifies more than 5 million protein pairs predicting 94,009 new interactions with high confidence. We experimentally tested a subset of these predictions using yeast two-hybrid analysis and affinity purification followed by quantitative mass spectrometry. Thus we identified 462 new protein-protein interactions and confirmed the predictive power of the network. These independent experiments address potential issues of circular reasoning and are a distinctive feature of this work. Analysis of the physical interactome unravels subnetworks mediating between different functional and physical subunits of the cell. Finally, we demonstrate the utility of the network for the analysis of molecular mechanisms of complex diseases by applying it to genome-wide association studies of neurodegenerative diseases. This analysis provides new evidence implying TOMM40 as a factor involved in Alzheimer's disease. The network provides a high-quality resource for the analysis of genomic data sets and genetic association studies in particular. Our interactome is available via the hPRINT web server at: www.print-db.org.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.