A new functional association-based protein complex prediction

Protein complexes serve as functional modules in various biological processes. Computational predication of protein complexes is one of the most important challenges in the post-genomic era. In this paper, we take into account the biological function of proteins to reconstruct protein-protein interaction networks and propose a functional association-based method (FABM) to predict protein complexes in S. cerevisiae. The results show that FABM outperforms MCODE, MCL, and SPICi in identifying non-overlapping protein complexes. Reconstruction of the PPI network as a preprocessing step also helps to improve the performance of other graph clustering algorithms.