MILVA: an interactive tool for the exploration of multidimensional microarray data.
BACKGROUND
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.


BACKGROUND
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.
D'Alimonte
Davide
D
Neural Computing Research Group, Aston University, Aston Triangle, Birmingham, UK.
Lowe
David
D
Nabney
Ian T
IT
Mersinias
Vassilis
V
Smith
Colin P
CP
D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D003196:Computer Graphics; D003627:Data Interpretation, Statistical; D005786:Gene Expression Regulation; D020407:Internet; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010363:Pattern Recognition, Automated; D011336:Probability; D011381:Programming Languages; D012680:Sensitivity and Specificity; D016415:Sequence Alignment; D017422:Sequence Analysis, DNA; D012984:Software; D014584:User-Computer Interface