apComplex

apComplex estimates bipartite graphs of protein complex membership from affinity-purification/mass-spectrometry (AP-MS) data to model protein–protein interactions and macromolecular complex assembly.

Key Features:

• Bipartite graph estimation: Estimates bipartite graphs representing protein complex membership using AP-MS data.
• Local modeling methodology: Implements the local modeling approach proposed by Scholtens and Gentleman (2004) to focus on local complex structure rather than a static global interactome.
• Integration of Y2H and AP-MS data: Combines yeast two-hybrid (Y2H) and AP-MS datasets to leverage complementary information for interaction mapping.
• Bait selection considerations: Explicitly accounts for the impact of bait selection on the interpretability of complex membership estimates.
• Systems biology relevance: Supports analyses relevant to functional annotation, prediction of new complexes, pathway interactivity, and coordination with gene-expression data.
• Interactome sensitivity and specificity: Addresses issues of completeness, sensitivity, and specificity inherent in Y2H and AP-MS technologies.

Scientific Applications:

• Protein complex modeling: Characterizes assembly and membership of macromolecular protein complexes from high-throughput AP-MS data.
• Interactome data analysis: Evaluates and integrates Y2H and AP-MS data to improve coverage and accuracy of interaction maps.
• Functional annotation and pathway analysis: Facilitates assignment of protein function and exploration of pathway interactivity using complex membership information and gene-expression coordination.
• Prediction of novel complexes: Identifies candidate new protein complexes through local interaction patterns and integrated datasets.

Methodology:

Computational steps explicitly include estimation of bipartite graphs from AP-MS data, integration of Y2H and AP-MS datasets, and application of the local modeling methodology of Scholtens and Gentleman (2004), with explicit consideration of bait selection effects.