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oai:digital.library.adelaide.edu.au:2440/1179122026-06-12T08:09:54Zcom_2440_14759col_2440_14760

Barry, Simon Glonek, Gary Pederson, Stephen Martin Adelaide Medical School 2018 http://hdl.handle.net/2440/117912 The development of Affymetrix Exon Arrays was a signifcant step forward from 3' Microarray technology, however detection of alternate splicing events proved challenging. In this work a novel method, Bayesian Modelling for Exon Arrays (BMEA), is described which shows an improvement in performance over previous approaches, and fits a more appropriate model for each gene using an MCMC process. Applying BMEA to an in-house dataset contrasting resting and stimulated Treg and Th cells, shed signifcant new light into key mechanisms involved in regulation of the T cell activation response. Thesis (Ph.D.) -- University of Adelaide, Adelaide Medical School, 2018 en Microarray bioinformatics Bayesian statistics regulatory T cells BMEA: Bayesian Modelling For Exon Array Data Thesis This electronic version is made publicly available by the University of Adelaide in accordance with its open access policy for student theses. Copyright in this thesis remains with the author. This thesis may incorporate third party material which has been used by the author pursuant to Fair Dealing exceptions. If you are the owner of any included third party copyright material you wish to be removed from this electronic version, please complete the take down form located at: http://www.adelaide.edu.au/legalsopen.access