Graph based unsupervised feature selection for microarray data

Tripti Swarnkar; Pabitra Mitra

doi:10.1109/BIBMW.2012.6470231

2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)

Graph based unsupervised feature selection for microarray data

Year: 2012, Pages: 750-751

DOI Bookmark: 10.1109/BIBMW.2012.6470231

Authors

Tripti Swarnkar, Depatment of Computer Science & Engineering, Indian Institue of Technology, Kharagpur - 721302, India
Pabitra Mitra, Depatment of Computer Science & Engineering, Indian Institue of Technology, IIT, Kharagpur - 721302, India

Abstract

Gene selection is an important step in microarray data analysis. In this paper we present an unsupervised feature selection technique for this purpose. The method constructs multiview graph based representation of samples using expression values gene sub clusters. Such individual views are further clustered using graph clustering techniques. We evaluate our technique using classification accuracies obtained from selecting representative genes from each such clusters.

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Graph based unsupervised feature selection for microarray data

Authors

Abstract

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