Introducing the Concept of Second Neighbours to FPNC algorithm for Improving the Functional Modules Detection

Proteins are biological polymers of amino acid residues. Proteins perform various functions within living organisms. Multiple proteins carry out these tasks by forming functional modules. Each functional module possesses community structure. For identifying functional modules, a lot of community detection or clustering algorithms were designed, but most of those algorithms suffer by inappropriate clustering results which do not make any sense biologically. Though some of the algorithms came out with better results but too high time complexity was not of great help. Recently an efficient algorithm was designed which outperformed other existing algorithms, named Fast Protein Network Clustering or FPNC algorithm. We have worked on that algorithm and improved its performance by introducing the concept of second neighbours (neighbours of neighbours of any vertex), named as Second order Fast Protein Network Clustering algorithm or 2nd order FPNC algorithm. By coming up with the concept of 2nd neighbours, 2nd order FPNC algorithm has better scoring function and better functional module mapping results indicating efficient identification of functional modules from any protein-protein Interaction network. These results have also shown that 2nd order FPNC algorithm identifies the functional modules more accurately than existing algorithms. According to computational results 2nd order FPNC algorithm put an important pace in the field of functional modules detection from protein-protein interaction networks.