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C-MICRA: A Tool for Clustering Microarray Data

C-MICRA: A Tool for Clustering Microarray Data
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Author(s): Emmanuel Udoh (Sullivan University, USA)and Salim Bhuiyan (Indiana University–Purdue University, USA)
Copyright: 2009
Pages: 8
Source title: Handbook of Research on Innovations in Database Technologies and Applications: Current and Future Trends
Source Author(s)/Editor(s): Viviana E. Ferraggine (UNICEN, Argentina), Jorge Horacio Doorn (UNICEN, Argentina)and Laura C. Rivero (UNICEN, Argentina)
DOI: 10.4018/978-1-60566-242-8.ch061

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Abstract

In the field of bioinformatics, small to large data sets of genes, proteins, and genomes are analyzed for biological significance. A technology that has been in the forefront of generating large amounts of gene data is the microarray or hybridization technique. It has been instrumental in the success of the human genome project and paved the way for a new era of genetic screening, testing, and diagnostics (Scheena, 2003). The microarray data set can be made of thousands of rows and columns. It often contains missing values, exhibits high-dimensional attributes, and is generally too large for manual management or examination (Tseng & Kao, 2005; Turner, Bailey, Krzanowski, & Hemingway, 2005). Database technology is necessary for the extraction, sorting, and analyzing of microarray data sets.

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