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Clustering microarray time-series data using expectation maximization and multiple profile alignment

Subhani, Numanul; Rueda, Luis; Ngom, Alioune; Burden, Conrad


A common problem in biology is to partition a set of experimental data into clusters in such a way that the data points within the same cluster are highly similar while data points in different clusters are very different. In this direction, clustering microarray time-series data via pairwise alignment of piece-wise linear profiles has been recently introduced. We propose a EM clustering approach based on a multiple alignment of natural cubic spline representations of gene expression profiles....[Show more]

CollectionsANU Research Publications
Date published: 2009
Type: Conference paper
Source: Proceedings - 2009 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2009
DOI: 10.1109/BIBMW.2009.5332128


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