Sparse Bayesian promoter based gene classification

K. K. Lee, G. C. Cawley, M. W. Bevan

Research output: Contribution to conferencePaper

Abstract

A method to distinguish between co-regulated genes that are up- or down-regulated under a given treatment, based on the composition of the upstrem promoter region, would be a valuable tool in deciphering gene regulatory networks. Ideally, the classification should be based on a small number of regulatory motifs, whos presence in the promoter region of a gene induce a significant effect on its transcriptional regulation. In this paper, we investigate the use of Relevance Vector Machines for this task, and present initial results of an analysis of glucose response in the model plant Arabidopsis thaliana, that has revealed novel biological information.
Original languageEnglish
Pages527-532
Number of pages6
Publication statusPublished - Apr 2005
EventProceedings of the European Symposium on Artificial Neural Networks (ESANN-2005) - Bruges, Belgium
Duration: 27 Apr 200529 Apr 2005

Conference

ConferenceProceedings of the European Symposium on Artificial Neural Networks (ESANN-2005)
CountryBelgium
CityBruges
Period27/04/0529/04/05

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