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2006
Springer

A New Profile Alignment Method for Clustering Gene Expression Data

9 years 5 months ago
A New Profile Alignment Method for Clustering Gene Expression Data
We focus on clustering gene expression temporal profiles, and propose a novel, simple algorithm that is powerful enough to find an efficient distribution of genes over clusters. We also introduce a variant of a clustering index that can effectively decide upon the optimal number of clusters for a given dataset. The clustering method is based on a profilealignment approach, which minimizes the mean-square-error of the first order differentials, to hierarchically cluster microarray time-series data. The effectiveness of our algorithm has been tested on datasets drawn from standard experiments, showing that our approach can effectively cluster the datasets based on profile similarity.
Ataul Bari, Luis Rueda
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2006
Where AI
Authors Ataul Bari, Luis Rueda
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