methods that directly mine for dense subnetworks from the PPI network make use of solely the topology of the network.
Molecular COmplex DEtection (MCODE)
MCODE, proposed by Bader and Hogue [2003], is one of the first computational methods developed for protein complex detection from PPI networks. The MCODE algorithm operates in two steps, vertex weighting and complex prediction, and an optional third step for post-processing of the candidate complexes. In the first step, each protein v in the PPI network G is weighted based on its clustering coefficient (CC). However, instead of using the entire neighborhood of v, MCODE uses the density of the highest k-core in the neighborhood of v, which amplifies the weights for proteins located in densely connected regions of G. A k-core is a subnetwork of proteins such that each protein in this subnetwork has a degree no less than k. A k-core in the neighborhood of v is a subnetwork of v and all its neighbors that have degree no less than k. A k-core in the neighborhood of v is highest or maximal if there exists no (k + 1)-core in that neighborhood. If Ck(v) represents this highest k-core, the weight for v is assigned as:
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