Integrating external biological knowledge in the construction of regulatory networks from time-series expression data

Table 5 Assessment result for the different methods applied to data sets generated in the stimulation study

Method	Data used	Network size	p-value of chi sq test^a	TPR (%)^b	# mis-class.^c	TP
iBMA-prior	Generated data + prior probability matrix	14011	<1.00E-320	71.13	16029	9966
iBMA-shortlist	Generated data + prior probability matrix	30753	<1.00E-320	47.23	23652	14526
iBMA-size	Generated data only	9349	<1.00E-320	20.31	27503	1899
iBMA-noprior	Generated data only	29393	<1.00E-320	8.55	46317	2513

^a The p-value of Pearson’s chi-square test measures the strength of association between an inferred network and the true network for the simulation study.
^b True positive rate (TPR) is defined as the proportion of correctly inferred regulatory relationships.
^c The number of misclassified cases is the sum of false positives and false negatives.
Remark: The values reported in the table were averaged across the 20 replications. The true network for the simulation study contained a total of 21951 edges.

ISSN: 1752-0509