Protein complexes identification and key proteins screening based on the ClusterONE and SSF algorithms

Detection of protein complexes and key proteins from protein-protein interaction networks is an important research direction in Bioinformatics and Systems Biology, which has attracted researchers' attention in the past decades. However, mature algorithms for detecting statistically significant protein complexes are still very limited. Two algorithms gain popularity in recent years and they are the ClusterONE and SSF algorithms. The ClusterONE has the advantages of high accuracy and low time complexity, while the SSF is a protein complexes detection method based on the Fisher exact test, which has the advantages of less information and high accuracy. In this paper, we have used ClusterONE and SSF algorithms to complete the screening of protein complexes. Our results demonstrate a key protein prediction algorithm based on protein centrality ordering and activation of the Tanh function. By combining the recognition of protein complexes with the screening of key proteins, the selected key proteins appeared with stronger reliability, thus providing an excellent contribution to protein Bioinformatics.