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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
ISBN13: 9781609604912|ISBN10: 1609604911|EISBN13: 9781609604929
DOI: 10.4018/978-1-60960-491-2.ch007
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MLA

Tchagang, Alain B., et al. "Biclustering of DNA Microarray Data: Theory, Evaluation, and Applications." Handbook of Research on Computational and Systems Biology: Interdisciplinary Applications, edited by Limin Angela Liu, et al., IGI Global, 2011, pp. 148-186. https://doi.org/10.4018/978-1-60960-491-2.ch007

APA

Tchagang, A. B., Pan, Y., Famili, F., Tewfik, A. H., & Benos, P. V. (2011). Biclustering of DNA Microarray Data: Theory, Evaluation, and Applications. In L. Liu, D. Wei, Y. Li, & H. Lei (Eds.), Handbook of Research on Computational and Systems Biology: Interdisciplinary Applications (pp. 148-186). IGI Global. https://doi.org/10.4018/978-1-60960-491-2.ch007

Chicago

Tchagang, Alain B., et al. "Biclustering of DNA Microarray Data: Theory, Evaluation, and Applications." In Handbook of Research on Computational and Systems Biology: Interdisciplinary Applications, edited by Limin Angela Liu, et al., 148-186. Hershey, PA: IGI Global, 2011. https://doi.org/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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