A clustering algorithm using Particle Swarm Optimization for DNA chip data analysis

Abstract

As DNA chips are becoming increasingly popular as a convenient way to perform vast amounts of experiments related to genes on a single chip, the importance of analyzing the data that is provided by such DNA chips is becoming significant. A very important analysis on DNA chip data would be clustering genes to identify gene groups which have similar properties. Clustering data for DNA chips usually deal with a large search space and has a very fuzzy characteristic. This task can be achieved by applying a clustering technique that mimics the biological world. One such algorithm is the Particle Swarm Optimization algorithm which was recently proposed as a very good candidate to solve such problems. In this paper, we propose a clustering mechanism that is based on the Particle Swarm Optimization algorithm. Our experiments show that the PSO-based clustering algorithm developed can efficiently cluster DNA chip data, and thus be used to extract valuable information from DNA chip data in an accurate yet timely manner. Copyright 2009 ACM.