Bioinformatics Advance Access published online on September 13, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti676
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1 Neural Computing Research Group, Aston University, Aston Triangle, Birmingham B4 7ET, United Kingdom
* 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 suggests 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 here presented 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 available1. 1 The MILVA software is currently available for Windows platform only. The software and the related documentation can be downloaded from http://www.ncrg.aston.ac.uk/Projects/milva.php Use "surrey" as username and "3245" as password to login.
Received July 1, 2005
Revised August 23, 2005
Accepted September 8, 2005
Applications note
MILVA: an interactive tool for the exploration of multidimensional microarray data
2 School of Biomedical and Molecular Sciences, University of Surrey, Guildford GU2 XH, United Kingdom
David Lowe, E-mail: d.lowe{at}aston.ac.uk
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