Format

Send to

Choose Destination
Genome Biol. 2012 Aug 31;13(8):R76. doi: 10.1186/gb-2012-13-8-r76.

A computational framework for boosting confidence in high-throughput protein-protein interaction datasets.

Abstract

Improving the quality and coverage of the protein interactome is of tantamount importance for biomedical research, particularly given the various sources of uncertainty in high-throughput techniques. We introduce a structure-based framework, Coev2Net, for computing a single confidence score that addresses both false-positive and false-negative rates. Coev2Net is easily applied to thousands of binary protein interactions and has superior predictive performance over existing methods. We experimentally validate selected high-confidence predictions in the human MAPK network and show that predicted interfaces are enriched for cancer -related or damaging SNPs. Coev2Net can be downloaded at http://struct2net.csail.mit.edu.

PMID:
22937800
PMCID:
PMC4053744
DOI:
10.1186/gb-2012-13-8-r76
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for BioMed Central Icon for PubMed Central
Loading ...
Support Center