Open AccessA temporal switch model for estimating transcriptional activity in gene expression
Author(s) -
Dafyd J. Jenkins,
Bärbel Finkenstädt,
D.A.J. Rand
Publication year - 2013
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btt111
Subject(s) - computer science , computational biology , markov chain monte carlo , transcription (linguistics) , bayesian probability , markov chain , dna microarray , reversible jump markov chain monte carlo , biology , gene expression , gene , genetics , machine learning , artificial intelligence , linguistics , philosophy
The analysis and mechanistic modelling of time series gene expression data provided by techniques such as microarrays, NanoString, reverse transcription-polymerase chain reaction and advanced sequencing are invaluable for developing an understanding of the variation in key biological processes. We address this by proposing the estimation of a flexible dynamic model, which decouples temporal synthesis and degradation of mRNA and, hence, allows for transcriptional activity to switch between different states.
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