Technical Reports

Mining Gene Expression Datasets using Density-based Clustering

IMSC-04-002 PDF Version of Full Report
      Seokkyung Chung, Jongeun Jun, Dennis McLeod

Abstract:
Given the recent advancement of microarray technologies, we present a density-based clustering approach for the purpose of co-expressed gene cluster identification. The underlying hypothesis is that a set of co-expressed gene clusters can be used to reveal a common biological function. By addressing the strengths and limitations of previous density-based clustering approaches, we present a novel clustering algorithm that utilizes a neighborhood defined by k-nearest neighbors. Experimental results indicate that the proposed method identifies biologically meaningful and co-expressed gene clusters.