Multi-faceted Functional Decomposition

In this chapter, we present a ppi decomposition algorithm called FACETS [1] in order to make sense of the deluge of interaction data using go annotation data. A key distinguishing feature of FACETS is that it finds not just a single functional decomposition of the ppi network, but a multi-faceted atlas of functional decompositions that portray alternative perspectives of the functional landscape of the underlying ppi. Each facet in the atlas represents a distinct interpretation of how the network can be functionally decomposed and organized. Specifically, the FACETS algorithm maximizes interpretative value of the atlas by optimizing inter-facet orthogonality and intra-facet cluster modularity.