Expression levels of mRNA molecules are regulated by different processes, comprising inhibition or activation by transcription factors and post-transcriptional degradation by microRNAs. birta (Bayesian Inference of Regulation of Transcriptional Activity) uses the regulatory networks of TFs and miRNAs together with mRNA and miRNA expression data to predict switches in regulatory activity between two conditions. A Bayesian network is used to model the regulatory structure and Markov-Chain-Monte-Carlo is applied to sample the activity states.
|Author||Benedikt Zacher, Khalid Abnaof, Stephan Gade, Erfan Younesi, Achim Tresch, Holger Froehlich|
|Date of publication||None|
|Maintainer||Benedikt Zacher <firstname.lastname@example.org>, Holger Froehlich <email@example.com>|
|License||GPL (>= 2)|
birta-methods: Methods for Function 'birta' in Package 'birta'
birta-package: Joint Bayesian Inference of miRNA and Transcription Factor...
birta.run: Main interface for Bayesian Inference of Regulation of...
EColiNetwork: Example TF-target graph from Regulon DB.
EColiOxygen: Example data set from E. Coli to sample TF activities.
genesets: TF-target and miRNA-target networks for simulated example.
get_potential_swaps: Calculate swap partner for TF-/miRNA-target graph.
limmaAnalysis: Perform a limma analysis on expression data.
limmaAnalysis-methods: Methods for Function 'limmaAnalysis' in Package 'birta'
plotConvergence: Plotting the likelihood along MCMC sampling.
potential_swaps: Potential swap moves for TF-target and miRNA-target networks...
sim: Simulated expression data for mRNAs and miRNAs.
TFexpr: Transcription factor expression values for the...