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

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

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.
Original languageEnglish
Pages (from-to)4192-4193
Number of pages2
JournalBioinformatics
Volume21
Issue number22
Early online date13 Sep 2005
DOIs
Publication statusPublished - 2005

Keywords

  • cluster analysis
  • computational biology
  • computer graphics
  • statistical data interpretation
  • gene expression regulation
  • Internet
  • oligonucleotide array sequence analysis
  • automated pattern recognition
  • probability
  • programming languages
  • sensitivity and specificity
  • sequence alignment
  • DNA sequence analysis
  • software
  • user-computer interface

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