Abstract
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 method 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 and with a criterion to determine the number of clusters.
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Mouysset, S., Guivarch, R., Noailles, J., Ruiz, D. (2012). Parallel Spectral Clustering for the Segmentation of cDNA Microarray Images. In: Rocha, M., Luscombe, N., Fdez-Riverola, F., RodrÃguez, J. (eds) 6th International Conference on Practical Applications of Computational Biology & Bioinformatics. Advances in Intelligent and Soft Computing, vol 154. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28839-5_1
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DOI: https://doi.org/10.1007/978-3-642-28839-5_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28838-8
Online ISBN: 978-3-642-28839-5
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