Knowledge Discovery in Microarray Gene Expression Data
DNA Microarrays are revolutionizing molecular biology, allowing simultaneous
analysis of many thousands of genes. Microarray hold the promise of important applications,
including creating novel, genetic-based diagnostic tests, finding new molecular targets for
therapy, and developing personalized treatments. Microarrays allow analysis of dynamic
processes and deeper insight into biological pathways. However, the large number of genes
and a typically small number of samples, present unique challenges for DNA microarray data
analysis. We discuss issues in normalization of microarray data, selecting the best set of
genes for classification and clustering, randomization techniques, and building classification
and clustering models. We illustrate these processes using a number of software tools and
show new results with potential biological significance.
DNA, Microarrays, molecular, biology, clustering.