An effective density-based hierarchical clustering technique to identify coherent patterns from gene expression data

Authors:
Sauravjyoti Sarmah;Rosy Das Sarmah;Dhruba Kumar Bhattacharyya
Affiliations:
Dept. of Comp Sc & Engg., Tezpur University, Napaam, India;Dept. of Comp Sc & Engg., Tezpur University, Napaam, India;Dept. of Comp Sc & Engg., Tezpur University, Napaam, India
Venue:
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
Year:
2011

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Abstract

We present an effective tree-based clustering technique (Gene ClusTree) for finding clusters over gene expression data. GeneClusTree attempts to find all the clusters over subspaces using a tree-based density approach by scanning the whole database in minimum possible scans and is free from the restrictions of using a normal proximity measure [1]. Effectiveness of GeneClusTree is established in terms of well known z-score measure and p-value over several real-life datasets. The p-value analysis shows that our technique is capable in detecting biologically relevant clusters from gene expression data.