DocumentCode :
3734143
Title :
Microarray data clustering and visualization tool using self-organizing maps
Author :
Zach Andrei Marasigan;Abigaile Dionisio;Geoffrey Solano
Author_Institution :
Univ. of the Philippines, Manila, Philippines
fYear :
2015
fDate :
7/1/2015 12:00:00 AM
Firstpage :
1
Lastpage :
5
Abstract :
Microarray is one of the technologies used in the interdisciplinary science of Biolnformatics. Its primary objective is to discover biological knowledge among genes through their expressions. Gene expressions usually come in large and multidimensional 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. This tool can be used to analyze large data set by preprocessing, clustering, and visualizing two-color cDNA microarray data. It can therefore aid microarray researchers and practitioners in determining the initial properties of the data they study before proceeding to their actual experimentation onto their data.
Keywords :
"Data visualization","Gene expression","Self-organizing feature maps","Cancer","Image color analysis","Clustering algorithms"
Publisher :
ieee
Conference_Titel :
Information, Intelligence, Systems and Applications (IISA), 2015 6th International Conference on
Type :
conf
DOI :
10.1109/IISA.2015.7387955
Filename :
7387955
Link To Document :
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