In this paper, biological background of cells’ regulatory mechanisms as well as gene regulatory networks are described. The models applied to infer gene regulatory networks such as Boolean networks, dynamic Bayesian networks, graphical Gaussian models and the novel two-stage model based on integration of a priori biological knowledge are described. These inference models are applied on Arabidopsis thaliana time series gene expression data subset. To compare models inference capabilities, ROC and AUC value as validation criteria are used. Some further directions for inference of gene regulatory networks as well as microRNA-mediated networks and model development are given at the end of the paper.
reverse engineering, gene regulatory networks, bioinformatics, computational biology, model validation
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