Assessing the impact of non-additive noise on modelling transcriptional regulation with Gaussian processes

Davies, V. and Husmeier, D. (2013) Assessing the impact of non-additive noise on modelling transcriptional regulation with Gaussian processes. In: Muggeo, V.M.R., Capursi, V., Boscaino, G. and Lovison, G. (eds.) Proceedings of the 28th International Workshop on Statistical Modelling. Gruppo Istituto Poligrafico Europeo SRL, pp. 559-562. ISBN 9788896251492

Abstract

In transcriptional regulation, transcription factors (TFs) are often unobservable at mRNA level or may be controlled outside of the system being modelled. Gaussian processes are a promising approach for dealing with these difficulties as a prior distribution can be defined over the latent TF activity profiles and the posterior distribution inferred from the observed expression levels of potential target genes. However previous approaches have been based on the assumption of additive Gaussian noise to maintain analytical tractability. We investigate the influence of a more realistic form of noise on a biologically accurate system based on Michaelis-Menten kinetics.

• Item Type: Book Sections
• Status: Published
• Glasgow Author(s) Enlighten ID: Husmeier, Professor Dirk and Davies, Dr Vinny
• Authors: Davies, V., and Husmeier, D.
• College/School: College of Science and Engineering > School of Mathematics and Statistics > Statistics
• Publisher: Gruppo Istituto Poligrafico Europeo SRL
• ISBN: 9788896251492
• Copyright Holders: Copyright © 2013 Statistical Modelling Society
• Publisher Policy: Reproduced with the permission of the editor