SODA

Global gene expression analysis by combinatorial optimization

Ameur, Adam and Aurell, Erik and Carlsson, Mats and Westholm, Jakub Orzechowski (2004) Global gene expression analysis by combinatorial optimization. In Silico Biology, 4 (20). ISSN 1434-3207

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Official URL: http://www.bioinfo.de/isb/2004/04/0020/

Abstract

Generally, there is a trade-off between methods of gene expression analysis that are precise but labor-intensive, e.g. RT-PCR, and methods that scale up to global coverage but are not quite as quantitative, e.g. microarrays. In the present paper, we show how how a known method of gene expression profiling (K. Kato, Nucleic Acids Research 23, 3685-3690 (1995)), which relies on a fairly small number of steps, can be turned into a global gene expression measurement by advanced data post-processing, with potentially little loss of accuracy. Post-processing here entails solving an ancillary combinatorial optimization problem. Validation is performed on in silico experiments generated from the FANTOM data base of full-length mouse cDNA. We present two variants of the method. One uses state-of-the-art commercial software for solving problems of this kind, the other a code developed by us specifically for this purpose, released in the public domain under GPL license.

Item Type:Article
Uncontrolled Keywords:global gene expression, combinatorial optimization
ID Code:31
Deposited By:Vicki Carleson
Deposited On:18 Jan 2007
Last Modified:18 Nov 2009 15:51

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