Biological Network Clustering using Distance and Graphical Network Algorithm

Abstract

Clustering is a process of grouping together similar data items together based on certain percentage of similarity or certain amount of threshold value. The study of the protein-protein interaction is an important task as this is necessary in order to identify how the proteins are grouped together and how they interact with each other. This process of studying or identifying the protein-protein interaction so far done anciently is followed by the study of the clustering method. Out of the various clustering algorithms the k-means clustering algorithm holds good for the study of the protein-protein interaction. Our project work focuses on the drawbacks of the various k-means clustering algorithms and thereby focusing on the complete study of the protein-protein interaction, and develop a new clustering algorithm which will satisfy all the drawbacks of the k-means clustering and this algorithm will be an efficient algorithm for the purpose of studying and identifying the protein-protein interaction.

Keywords: k-means clustering, protein-protein interaction