Microarray data mining: A novel optimization-based approach to uncover biologically coherent structures |
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| Authors: | Meng P Tan Erin N Smith James R Broach Christodoulos A Floudas |
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| Institution: | (1) Department of Chemical Engineering, Princeton University, Princeton, NJ, USA;(2) Molecular and Cellular Biology Program, University of Washington, Washington, WA, USA;(3) Department of Molecular Biology, Princeton University, Princeton, NJ, USA |
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| Abstract: | Background DNA microarray technology allows for the measurement of genome-wide expression patterns. Within the resultant mass of data
lies the problem of analyzing and presenting information on this genomic scale, and a first step towards the rapid and comprehensive
interpretation of this data is gene clustering with respect to the expression patterns. Classifying genes into clusters can
lead to interesting biological insights. In this study, we describe an iterative clustering approach to uncover biologically
coherent structures from DNA microarray data based on a novel clustering algorithm EP_GOS_Clust. |
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