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The human disease network
- K. Goh, M. Cusick, D. Valle, B. Childs, M. Vidal, A. Barabasi
- BiologyProceedings of the National Academy of Sciences
- 22 May 2007
It is found that essential human genes are likely to encode hub proteins and are expressed widely in most tissues, suggesting that disease genes also would play a central role in the human interactome, and that diseases caused by somatic mutations should not be peripheral.
Towards a proteome-scale map of the human protein–protein interaction network
An initial version of a proteome-scale map of human binary protein–protein interactions is described, which increases by ∼70% the set of available binary interactions within the tested space and reveals more than 300 new connections to over 100 disease-associated proteins.
A Mitochondrial Protein Compendium Elucidates Complex I Disease Biology
Evidence for dynamically organized modularity in the yeast protein–protein interaction network
This work investigated how hubs might contribute to robustness and other cellular properties for protein–protein interactions dynamically regulated both in time and in space, and uncovered two types of hub: ‘party’ hubs, which interact with most of their partners simultaneously, and ‘date’ Hubs, which bind their different partners at different times or locations.
High-Quality Binary Protein Interaction Map of the Yeast Interactome Network
A comparative quality assessment of current yeast interactome data sets is carried out, demonstrating that high-throughput yeast two-hybrid (Y2H) screening provides high-quality binary interaction information.
Interactome Networks and Human Disease
A Map of the Interactome Network of the Metazoan C. elegans
A large fraction of the Caenorhabditis elegans interactome network is mapped, starting with a subset of metazoan-specific proteins, and more than 4000 interactions were identified from high-throughput, yeast two-hybrid screens.
Genome-scale analysis of in vivo spatiotemporal promoter activity in Caenorhabditis elegans
Automated comparison and clustering of the obtained in vivo expression patterns show that genes coexpressed in space and time tend to belong to common functional categories, enabling prediction of anatomical and temporal interaction territories between protein partners.
Uncovering disease-disease relationships through the incomplete interactome
A network-based framework to identify the location of disease modules within the interactome and use the overlap between the modules to predict disease-disease relationships is presented and it is found that disease pairs with overlapping disease modules display significant molecular similarity, elevated coexpression of their associated genes, and similar symptoms and high comorbidity.
The HUPO PSI's Molecular Interaction format—a community standard for the representation of protein interaction data
This work proposes a community standard data model for the representation and exchange of protein interaction data, jointly developed by members of the Proteomics Standards Initiative (PSI) and the Human Proteome Organization (HUPO).