An integrated tool for microarray data clustering and cluster validity assessment

In this paper we present a data mining system, which allows the application of different clustering and cluster validity algorithms for DNA microarray data. This tool may improve the quality of the data analysis results, and may support the prediction of the number of relevant clusters in the microa...

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Bibliographic Details
Published in:Bioinformatics Vol. 21; no. 4; pp. 451 - 455
Main Authors: Bolshakova, Nadia, Azuaje, Francisco, Cunningham, Pádraig
Format: Journal Article
Language:English
Published: England Oxford University Press 15.02.2005
Oxford Publishing Limited (England)
Subjects:
Algorithms
Benchmarking - methods
Cluster Analysis
Data mining
Database Management Systems
Deoxyribonucleic acid
DNA
Gene Expression Profiling - methods
Information Storage and Retrieval
Oligonucleotide Array Sequence Analysis - methods
Pattern Recognition, Automated - methods
Software
Systems Integration
User-Computer Interface
ISSN:1367-4803, 1460-2059, 1367-4811
Online Access:Get full text
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Summary:In this paper we present a data mining system, which allows the application of different clustering and cluster validity algorithms for DNA microarray data. This tool may improve the quality of the data analysis results, and may support the prediction of the number of relevant clusters in the microarray datasets. This systematic evaluation approach may significantly aid genome expression analyses for knowledge discovery applications. The developed software system may be effectively used for clustering and validating not only DNA microarray expression analysis applications but also other biomedical and physical data with no limitations. Availability: The program is freely available for non-profit use on request at http://www.cs.tcd.ie/Nadia.Bolshakova/Machaon.html Contact: Nadia.Bolshakova@cs.tcd.ie
Bibliography:istex:877A414C93751D92028648BCEFFEBE62AB58883D
To whom correspondence should be addressed.
ark:/67375/HXZ-GZCCRNTV-Z
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ISSN:1367-4803
1460-2059
1367-4811
DOI:10.1093/bioinformatics/bti190