Abstract
Mining microarray data to unearth interesting expression profile patterns for discovery of in silico biological knowledge is an emerging area of research in computational biology. A group of functionally related genes may have similar expression patterns under a set of conditions or at some time points. Biclustering is an important data mining tool that has been successfully used to analyze gene expression data for biologically significant cluster discovery. The purpose of this chapter is to introduce interesting patterns that may be observed in expression data and discuss the role of biclustering techniques in detecting interesting functional gene groups with similar expression patterns.
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Roy, S., Bhattacharyya, D.K., Kalita, J.K. (2015). Analysis of Gene Expression Patterns Using Biclustering. In: Guzzi, P. (eds) Microarray Data Analysis. Methods in Molecular Biology, vol 1375. Humana Press, New York, NY. https://doi.org/10.1007/7651_2015_280
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DOI: https://doi.org/10.1007/7651_2015_280
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