Clustering of Protein Sequences with a Modularity-Based Approach

Remote homology detection between protein sequences is a central problem in computational biology. This may help to identify functional and structural classes of proteins. This paper uses a modularity-based method, which maximizes the modularity of protein network to find the partitioning with strong community structure, for clustering protein sequences. The experiments based on the superfamily level of SCOP (Structure Classification of Proteins) database show that the approach is able to identify correctly the superfamilies to which the sequences belong.