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Bioinformatics Advance Access originally published online on September 13, 2005
Bioinformatics 2005 21(22):4192-4193; doi:10.1093/bioinformatics/bti676
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oxfordjournals.org

MILVA: An interactive tool for the exploration of multidimensional microarray data

Davide D'Alimonte 1, David Lowe 1,*, Ian T. Nabney 1, Vassilis Mersinias 2 and Colin P. Smith 2

1Neural Computing Research Group, Aston University Aston Triangle, Birmingham B4 7ET, UK
2School of Biomedical and Molecular Sciences, University of Surrey Guildford, Surrey GU2 7XH, UK

*To whom correspondence should be addressed.

Motivation: Clustering techniques such as k-means and hierarchical clustering are commonly used to analyze DNA microarray derived gene expression data. However, the interactions between processes underlying the cell activity suggest that the complexity of the microarray data structure may not be fully represented with discrete clustering methods.

Results: A newly developed software tool called MILVA (microarray latent visualization and analysis) is presented here to investigate microarray data without separating gene expression profiles into discrete classes. The underpinning of the MILVA software is the two-dimensional topographic representation of multidimensional microarray data. On this basis, the interactive MILVA functions allow a continuous exploration of microarray data driven by the direct supervision of the biologist in detecting activity patterns of co-regulated genes.

Availability: The MILVA software is freely available. The software and the related documentation can be downloaded from http://www.ncrg.aston.ac.uk/Projects/milva. User ‘surrey’ as username and ‘3245’ as password to login. The software is currently available for Windows platform only.

Contact: d.lowe{at}aston.ac.uk

Received on July 1, 2005; revised on August 23, 2005; accepted on September 8, 2005

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