PT  - JOURNAL ARTICLE
AU  - T Li
AU  - R Wernersson
AU  - RB Hansen
AU  - H Horn
AU  - JM Mercer
AU  - G Slodkowicz
AU  - CT Workman
AU  - O Rigina
AU  - K Rapacki
AU  - HH Stærfeldt
AU  - S Brunak
AU  - TS Jensen
AU  - K Lage
TI  - A scored human protein-protein interaction network to catalyze genomic interpretation
AID  - 10.1101/064535
DP  - 2016 Jan 01
TA  - bioRxiv
PG  - 064535
4099  - http://biorxiv.org/content/early/2016/07/26/064535.short
4100  - http://biorxiv.org/content/early/2016/07/26/064535.full
AB  - Human protein-protein interaction networks are critical to understanding cell biology and interpreting genetic and genomic data, but are challenging to produce in individual large-scale experiments. We describe a general computational framework that through data integration and quality control provides a scored human protein-protein interaction network (InWeb_IM). Juxtaposed with five comparable resources, InWeb_IM has 2.8 times more interactions (~585K) and a superior functional signal showing that the added interactions reflect real cellular biology. InWeb_IM is a versatile resource for accurate and cost-efficient functional interpretation of massive genomic datasets illustrated by annotating candidate genes from >4,700 cancer genomes and genes involved in neuropsychiatric diseases.