Subhani, Numanul; Rueda, Luis; Ngom, Alioune; Burden, Conrad
Motivation: Clustering gene expression data given in terms of time-series is a challenging problem that imposes its own particular constraints. Traditional clustering methods based on conventional similarity measures are not always suitable for clustering time-series data. A few methods have been proposed recently for clustering microarray time-series, which take the temporal dimension of the data into account. The inherent principle behind these methods is to either dene a similaritymeasure...[Show more]
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