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
Official URL: http://www.bioinfo.de/isb/2004/04/0020/
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.
|Uncontrolled Keywords:||global gene expression, combinatorial optimization|
|Deposited By:||Vicki Carleson|
|Deposited On:||18 Jan 2007|
|Last Modified:||18 Nov 2009 15:51|
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