摘要：Detecting known protein complexes and predicting undiscovered protein complexes from protein-protein interaction (PPI) networks help us to understand principles of cell organization and its functions. Nevertheless, the discovery of protein complexes based on experiment still needs to be explored. Therefore, computational methods are useful approaches to overcome the experimental limitations. Nevertheless, extraction of protein complexes from PPI network is often nontrivial. Two major constraints are large amount of noise and ignorance of occurrence time of different interactions in PPI network. In this paper, an efficient algorithm, Inter Module Hub Removal Clustering (IMHRC), is developed based on inter-module hub removal in the weighted PPI network which can detect overlapped complexes. By removing some of the inter-module hubs and module hubs, IMHRC eliminates high amount of noise in dataset and implicitly considers different occurrence time of the PPI in network. The performance of the IMHRC was evaluated on several benchmark datasets and results were compared with some of the state-of-the-art models. The protein complexes discovered with the IMHRC method show significantly better agreement with the real complexes than other current methods. Our algorithm provides an accurate and scalable method for detecting and predicting protein complexes from PPI networks.
