Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing

Table 2 A summary of results for system noise with standard deviation 1 and observation noise with standard deviation 0.1

(a) The number of true positives (# TP) and false positives (# FP) of estimated regulations in two network model by the proposed approach, ENet1, ENet2, G1DBN1, and G1DBN2 for equally and unequally spaced time series data. PRE denotes the precision of the results. Regulations in two networks are 305 in total. (b) The number of true positives (# TP) and false positives (# FP) of changes on regulations between two network models estimated by the proposed approach, ENet1, ENet2, G1DBN1, and G1DBN2 for equally and unequally spaced time series data. Since no changes are estimated by ENet2 and G1DBN2, their results are indicated by '-'. The regulations changed in two networks are in total 47.

ISSN: 1471-2164