Granger causality approaches and Bayesian network inference approaches applied on experimental data (small sample size). The experiment measures the intensity of 7 genes in two cases of Arabidopsis Leaf: mock (normal) and infected. (A)The time traces of 7 genes are plotted. There are 4 realizations of 24 time points. The time interval is 2 hours. (B) The network structures are derived by using dynamic Bayesian network inference. All the genes are numbered as shown. Interestingly, after infection, the total network structure is changed. (a) The network structure for mock case. (b) the network structure for infected case. (C) The network structures are derived by using Granger causality. (a) The network structure for mock case. (b) the network structure for infected case. (c) Using bootstrapping method to construct a 95% confidence intervals. For visualization purpose, all the directed edges are numbered and enumerate them into the table.