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The increase in the amount of available Protein-Protein Interaction (PPI) data enables us to develop computational methods for protein complex predictions. A protein complex is a group of proteins that interact with each other at the same time and place. The protein complex generally corresponds to a cluster in PPI Network (PPIN). However, clusters correspond not only to protein complexes but also to sets of proteins that interact dynamically with each other. As a result, conventional graph-theoretic clustering methods that disregard interaction dynamics show high false-positive rates in protein complex predictions.
A Simultaneous Protein Interaction Network (SPIN) is introduced to specify mutually exclusive interactions as indicated from the overlapping interfaces and to exclude competition from mutually exclusive interactions that arise during the detection of protein complexes. After constructing SPINs, naive clustering algorithms can be applied to the SPINs for protein c
