Sparse Bayesian promoter based gene classification

Lee, K. K., Cawley, G. C. and Bevan, M. W. (2005) Sparse Bayesian promoter based gene classification. In: Proceedings of the European Symposium on Artificial Neural Networks (ESANN-2005), 2005-04-27 - 2005-04-29.

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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.

Item Type: Conference or Workshop Item (Paper)
Faculty \ School: Faculty of Science > School of Computing Sciences

University of East Anglia > Faculty of Science > Research Groups > Computational Biology (subgroups are shown below) > Machine learning in computational biology
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Depositing User: Vishal Gautam
Date Deposited: 14 Jun 2011 15:05
Last Modified: 18 Mar 2020 08:02
URI: https://ueaeprints.uea.ac.uk/id/eprint/23867
DOI:

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