title: A novel protein complex identification algorithm based on Connected Affinity Clique Extension (CACE).
abstract: A novel algorithm based on Connected Affinity Clique Extension (CACE) for mining overlapping functional modules in protein interaction network is proposed in this paper. In this approach, the value of protein connected affinity which is inferred from protein complexes is interpreted as the reliability and possibility of interaction. The protein interaction network is constructed as a weighted graph, and the weight is dependent on the connected affinity coefficient. The experimental results of our CACE in two test data sets show that the CACE can detect the functional modules much more effectively and accurately when compared with other state-of-art algorithms CPM and IPC-MCE.
authors.forename: Peng
authors.initials: P
authors.lastname: Li
authors.forename: Tingting
authors.initials: T
authors.lastname: He
authors.forename: Xiaohua
authors.initials: X
authors.lastname: Hu
authors.forename: Junmin
authors.initials: J
authors.lastname: Zhao
authors.forename: Xianjun
authors.initials: X
authors.lastname: Shen
authors.forename: Ming
authors.initials: M
authors.lastname: Zhang
authors.forename: Yan
authors.initials: Y
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D005656:Fungal Proteins / Q000378:metabolism*; D025941:Protein Interaction Mapping / Q000379:methods*; D060066:Protein Interaction Maps
chemical_list: D005656:Fungal Proteins