Skip to main content
Fig. 1 | BMC Bioinformatics

Fig. 1

From: Gene regulatory network inference based on a nonhomogeneous dynamic Bayesian network model with an improved Markov Monte Carlo sampling

Fig. 1

Overall framework of dynamic Bayesian network modeling based on structure prediction: a Data are processed into the short time series data required by the model. b SNR hyperparameters, regression parameters, and variance parameters are updated through a Markov chain Monte Carlo sampling method. c The multi-change point process is updated by the Markov Chain Monte Carlo Sampling method. d A particle filter is constructed with a multivariate point process, and the network structure is resampled. e Network performance is assessed with standard F-score and AUPR measures, and an experimentally validated biological network

Back to article page

BMC Bioinformatics

ISSN: 1471-2105

Contact us