Clustering-based approaches to discovering and visualising microarray data patterns.
This article focuses on clustering techniques for the analysis of microarray data and discusses contributions and applications for the implementation of intelligent diagnostic systems and therapy design studies. Approaches to validating and visualising expression clustering results and software and other relevant resources to support clustering-based analyses are reviewed. Finally, this paper addresses current limitations and problems that need to be investigated for the development of an advanced generation of pattern discovery tools.
Azuaje
Francisco
F
School of Computing and Mathematics, University of Ulster at Jordanstown, Newtownabbey, UK. fj.azuaje@ieee.org
D005810:Multigene Family; D020411:Oligonucleotide Array Sequence Analysis