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On Clustering of Genes

  • Raja Loganantharaj
  • Satish Cheepala
  • John Clifford
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4031)

Abstract

The availability of microarray technology at an affordable price makes it possible to determine expression of several thousand genes simultaneously. Gene expression can be clustered so as to infer the regulatory modules and functionality of a gene relative to one or more of the annotated genes of the same cluster. The outcome of clustering depends on the clustering method and the metric being used to measure the distance. In this paper we study the popular hierarchal clustering algorithm and verify how many of the genes in the same cluster share functionality. Further, we will also look into the supervised clustering method for satisfying hypotheses and view how many of these genes are functionally related.

Keywords

Gene Ontology Cluster Method Minimum Span Tree Total Entropy Saccharomyces Genome Database 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Raja Loganantharaj
    • 1
  • Satish Cheepala
    • 2
  • John Clifford
    • 2
  1. 1.Bioinformatics Research LabUniversity of Louisiana at LafayetteLafayette
  2. 2.Department of Biochemistry and Molecular BiologyLSU Health Sciences Center and Feist-Weiller Cancer CenterShreveport

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