Deconvolution of Targeted Protein–Protein Interaction Maps

Current proteomic techniques allow researchers to analyze
chosen
biological pathways or an ensemble of related protein complexes at
a global level via the measure of physical protein–protein
interactions by affinity purification mass spectrometry (AP-MS). Such
experiments yield information-rich but complex interaction maps whose
unbiased interpretation is challenging. Guided by current knowledge
on the modular structure of protein complexes, we propose a novel
statistical approach, named BI-MAP, complemented by software tools
and a visual grammar to present the inferred modules. We show that
the BI-MAP tools can be applied from small and very detailed maps
to large, sparse, and much noisier data sets. The BI-MAP tool implementation
and test data are made freely available.