Please use this identifier to cite or link to this item: http://dspace.cas.upm.edu.ph:8080/xmlui/handle/123456789/66
Title: Microarray Data Clustering Using Self-Organizing Maps
Authors: Solano, Geoffrey A.
Marasigan, Zach Andrei V.
Keywords: Microarray
Gene Expression
Clustering
Self-Organizing Maps
Issue Date: Apr-2013
Abstract: Microarray is one of the technologies used in the interdisciplinary science of BioInformatics. Its primary objective is to discover biological knowledge among genes through their expressions. Gene expressions usually come in large and multi-dimensional data which makes computational and statistical analyses necessary. Clustering of microarray data is one of these. Grouping similar genes together unfolds relationships of the biological properties of the genes under specific condition and, if supported by visualization, serves as good decision support for researchers. MaSOM is a software that uses Self-Organizing Maps, an Artificial Neural Network suitable both for clustering and for visualization, as its clustering method. This tool can be used to analyse large data set by preprocessing, clustering, and visualizing two-color cDNA microarray data.
URI: http://cas.upm.edu.ph:8080/xmlui/handle/123456789/66
Appears in Collections:Computer Science SP

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