Statistical inference of regulatory networks for circadian regulation

DOI10.1515/sagmb-2013-0051zbMath1296.92011OpenAlexW1558471429WikidataQ45957011 ScholiaQ45957011MaRDI QIDQ461673

Andrej Aderhold, Marco Grzegorczyk, Dirk Husmeier

Publication date: 13 October 2014

Published in: Statistical Applications in Genetics and Molecular Biology (Search for Journal in Brave)

Full work available at URL: http://eprints.gla.ac.uk/95697/1/95697.pdf

zbMATH Keywords

ANOVAhierarchical Bayesian modelscircadian clockcomparative method evaluationregulatory network inference

Mathematics Subject Classification ID

General biostatistics (92B15)

Related Items

Targeting Bayes factors with direct-path non-equilibrium thermodynamic integration, Model selection for factorial Gaussian graphical models with an application to dynamic regulatory networks, A sparse hierarchical Bayesian model for detecting relevant antigenic sites in virus evolution, Approximate Bayesian inference in semi-mechanistic models, Combining gene expression data and prior knowledge for inferring gene regulatory networks via Bayesian networks using structural restrictions, Inferring bi-directional interactions between circadian clock genes and metabolism with model ensembles

Uses Software

• Bio-PEPA
• glasso
• BioBayes
• glmnet
• minet
• PMTK
• ARACNE
• gptk
• PRMLT

Cites Work

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