A Non-Homogeneous Dynamic Bayesian Network with Sequentially Coupled Interaction Parameters for Applications in Systems and Synthetic Biology

DOI10.1515/1544-6115.1761zbMath1296.92039OpenAlexW2106898243WikidataQ43575097 ScholiaQ43575097MaRDI QIDQ2922546

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/69291/1/69291.pdf

zbMATH Keywords

gene regulatory networksreversible jump Markov chain Monte CarloBayesian multiple changepoint processesBayesian regularizationnon-stationary gene expression time seriestime varying dynamic Bayesian networks

Mathematics Subject Classification ID

General biostatistics (92B15)

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Inferring dynamic gene regulatory networks with low-order conditional independencies -- an evaluation of the method ⋮ A non-homogeneous dynamic Bayesian network with a hidden Markov model dependency structure among the temporal data points ⋮ Bayesian state space models for dynamic genetic network construction across multiple tissues ⋮ Regularization of non-homogeneous dynamic Bayesian networks with global information-coupling based on hierarchical Bayesian models ⋮ Hierarchical estimation of parameters in Bayesian networks ⋮ Improving nonhomogeneous dynamic Bayesian networks with sequentially coupled parameters ⋮ Statistical inference of regulatory networks for circadian regulation ⋮ Inferring bi-directional interactions between circadian clock genes and metabolism with model ensembles

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