Biclustering of DNA Microarray Data: Theory, Evaluation, and Applications

Biclustering of DNA Microarray Data: Theory, Evaluation, and Applications

Alain B. Tchagang, Youlian Pan, Fazel Famili, Ahmed H. Tewfik, Panayiotis V. Benos
Copyright: © 2011 |Pages: 39
DOI: 10.4018/978-1-60960-491-2.ch007
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Abstract

In this chapter, different methods and applications of biclustering algorithms to DNA microarray data analysis that have been developed in recent years are discussed and compared. Identification of biological significant clusters of genes from microarray experimental data is a very daunting task that emerged, especially with the development of high throughput technologies. Various computational and evaluation methods based on diverse principles were introduced to identify new similarities among genes. Mathematical aspects of the models are highlighted, and applications to solve biological problems are discussed.
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Biclustering Of Dna Microarray Data

Quantitative gene expression measurements using microarrays were first performed by Schena et al. (1995) on 45 Arabidopsis thaliana genes and shortly after, on thousands of genes or even a whole genome (DeRisi et al., 1996; DeRisi et al., 1997). Since that time, various methods for the analysis of such data have been developed. This includes the biclustering techniques.

Key Terms in this Chapter

Biclustering: Class of clustering algorithms that perform clustering on the rows and columns of a data matrix at the same time. It is also known as co-clustering, two-dimensional clustering, or two-way clustering.

Tissue Samples: A part of an organism used for biological, medical or research testing, for example, a small piece of a tumor.

Bicluster: A subset of rows in a data matrix that exhibit similar behavior across a subset of columns.

DNA Microarray: A small solid support, usually a membrane or glass slide, on which sequences of DNA are fixed in an orderly manner. DNA microarrays are used to measure the expression of many genes simultaneously. It is also called DNA chip.

Gene Expression: It is the process by which information from a gene is used in the synthesis of a functional gene product. It can also be viewed as the level of activity of a gene or group of genes.

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