A proteome-scale map of the human interactome network

TL;DR: Understanding of the mechanisms of silencing is enhanced, making it possible to describe in molecular terms a continuum of direct interactions from miRNA target recognition to mRNA deadenylation, decapping and 5′-to-3′ degradation.

TL;DR: The aggregation and analysis of high-quality exome (protein-coding region) sequence data for 60,706 individuals of diverse ethnicities generated as part of the Exome Aggregation Consortium (ExAC) provides direct evidence for the presence of widespread mutational recurrence.

TL;DR: Using high-throughput affinity-purification mass spectrometry, BioPlex is used to identify interacting partners for 2,594 human proteins in HEK293T cells and reveals associations among thousands of protein domains, suggesting a basis for examining structurally related proteins.

TL;DR: 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.

TL;DR: The FLI 1 level was not predictive of remission attainment, but patients with low or high FLI1 expression had shorter remission duration and overall survival.

TL;DR: The findings point to multiple loci with moderate effects associated with susceptibility to prostate cancer that, taken together, in the future may predict high risk in select individuals.

TL;DR: This article showed that a significant fraction of the protein-protein interactions in genome-wide datasets, as well as many of the individual interactions reported in the literature, are inconsistent with the known 3D structures of three recent complexes (RNA polymerase II, Arp2/3 and the proteasome).

TL;DR: Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual geno-phenotypes.