Segmentation of cDNA microarray images using parallel spectral clustering

Microarray technology generates large amounts of expression level of genes to be analyzed simultaneously. This analysis implies microarray image segmentation to extract the quantitative information from spots. Spectral clustering is one of the most relevant unsupervised methods able to gather data w...

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Bibliographic Details
Published in:Advances in distributed computing and artificial intelligence journal 2013, Vol.2 (13), p.1-8
Main Authors: Mouysset, Sandrine, Guivarch, Ronan, Noailles, Joseph, Ruiz, Daniel
Format: Article
Language:English
Subjects:
Computer Science
Distributed, Parallel, and Cluster Computing
Online Access:Get full text
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Summary:Microarray technology generates large amounts of expression level of genes to be analyzed simultaneously. This analysis implies microarray image segmentation to extract the quantitative information from spots. Spectral clustering is one of the most relevant unsupervised methods able to gather data without a priori information on shapes or locality. We propose and test on microarray images a parallel strategy for the Spectral Clustering method based on domain decomposition with a criterion to determine the number of clusters.
ISSN:2255-2863
2255-2863