Detecting temporal protein complexes based on Neighbor Closeness and time course protein interaction networks

The detection of temporal protein complexes would be a great aid in furthering our knowledge of the dynamic features and molecular mechanism in cell life activities. Inspired by the idea of that the tighter a protein's neighbors inside a module connect, the greater the possibility that the protein belongs to the module, we propose a novel clustering algorithm CNC (Clustering based on Neighbor Closeness) and apply it to the time course protein interaction networks (TCPINs) to detect temporal protein complexes. Our novel algorithm has better performance on identifying protein complexes than five state-of-the-art algorithms¿Hunter, MCODE, CFinder, SPICI, and ClusterONE¿in terms of matching degree and accuracy metric, meanwhile it obtains many protein complexes with strong biological significance.