Deconvolution of targeted protein-protein interaction maps

J Proteome Res. 2012 Aug 3;11(8):4102-9. doi: 10.1021/pr300137n. Epub 2012 Jul 10.


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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Autophagy
  • Bayes Theorem
  • Cluster Analysis
  • Computer Simulation
  • Data Interpretation, Statistical
  • Humans
  • Likelihood Functions
  • Markov Chains
  • Models, Biological
  • Monte Carlo Method
  • Multiprotein Complexes / physiology
  • Protein Binding
  • Protein Interaction Maps*
  • Proteomics
  • Software*


  • Multiprotein Complexes