Fast protein network clustering algorithm: a new approach for clustering protein-protein interaction networks to detect functional modules

Proteins are responsible for health disorder, evolution of species. These tasks are carried out by forming functional modules. Each functional module possesses community structure. For identifying the functional modules, a lot of community detection or clustering algorithms are designed, but most of the algorithms suffer by either high computational time or inappropriate clustering results. We propose an algorithm based on relative vertex-to-vertex clustering value and agglomerative hierarchical method, known as Fast Protein Network Clustering algorithm. It is faster than existing algorithms and resolves the most common clustering problem-clustering any vertex (protein) of degree one from its neighbour. We also tested our algorithm with the most popular four algorithms in respect to functional module mapping and efficiency analysis. FPNC algorithm successfully outperformed existing algorithms which is the current state-of-the-art agglomerative approach to functional module identification.