HIPPIE: Integrating protein interaction networks with experiment based quality scores.

PloS One
Martin H SchaeferMiguel A Andrade-Navarro

Abstract

Protein function is often modulated by protein-protein interactions (PPIs) and therefore defining the partners of a protein helps to understand its activity. PPIs can be detected through different experimental approaches and are collected in several expert curated databases. These databases are used by researchers interested in examining detailed information on particular proteins. In many analyses the reliability of the characterization of the interactions becomes important and it might be necessary to select sets of PPIs of different confidence levels. To this goal, we generated HIPPIE (Human Integrated Protein-Protein Interaction rEference), a human PPI dataset with a normalized scoring scheme that integrates multiple experimental PPI datasets. HIPPIE's scoring scheme has been optimized by human experts and a computer algorithm to reflect the amount and quality of evidence for a given PPI and we show that these scores correlate to the quality of the experimental characterization. The HIPPIE web tool (available at http://cbdm.mdc-berlin.de/tools/hippie) allows researchers to do network analyses focused on likely true PPI sets by generating subnetworks around proteins of interest at a specified confidence level.

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Citations

Jun 13, 2014·PLoS Computational Biology·Martin H SchaeferChristina Kiel
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Methods Mentioned

BETA
two hybrid
X-ray
FRET
tandem affinity purification
Y2H
affinity capture

Software Mentioned

TAP
iRefWeb
IntAct
HIPPIE
HPRD
HomoMINT
BIND
MIPS
MINT
PSICQUIC

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