Alignment of Microarray Data

Abstract

The aim in microarray data analysis is to discover patterns of gene expression and to identify similar genes. Simply comparing new gene sequences to known DNA sequences often does not reveal the function of a new gene; thus, more sophisticated techniques are in order. Nowadays, data mining techniques, and in particular the clustering process, play an important role in bioinformatics. To analyze vast amounts of data can be difficult; thus, a way to cluster similar data is needed. This chapter is devoted to illustrate the general data mining approach used in microarray data analysis, combining clustering, alignment and similarity, and to highlight a novel similarity measure capable of capturing hidden correlations between data.

Keywords: Data analysis; Edit distance; Microarray; Multiparameterized edit distance; Sequence alignment.