JOURNAL ARTICLE

Microarray data clustering and visualization tool using self-organizing maps

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:
Cluster analysis Visualization Computer science Data mining Microarray databases Preprocessor Data visualization Gene chip analysis Self-organizing map Set (abstract data type) Microarray analysis techniques Software Data set Information visualization Data pre-processing Artificial intelligence Microarray Gene Biology

Metrics

4
Cited By
0.58
FWCI (Field Weighted Citation Impact)
22
Refs
0.71
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Gene expression and cancer classification
Life Sciences →  Biochemistry, Genetics and Molecular Biology →  Molecular Biology
Bioinformatics and Genomic Networks
Life Sciences →  Biochemistry, Genetics and Molecular Biology →  Molecular Biology
Machine Learning in Bioinformatics
Life Sciences →  Biochemistry, Genetics and Molecular Biology →  Molecular Biology
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