BMC Bioinformatics

Table 14 Best links F-scores of YEASTRACT subnetworks using our proposed algorithm with D-CLINDE and GlobalMIT+

From: High-order dynamic Bayesian Network learning with hidden common causes for causal gene regulatory network

			D-CLINDE			GlobalMIT+
sn	n	n _L	Complete	Hidden	IgnoreHidden	Complete	Hidden	IgnoreHidden
sn1	4	5	0.600	0.571	0.571	0.286	0.500	0.267
sn2	5	11	0.533	0.429	0.429	0.453	0.659	0.421
sn3	6	5	0.333	0.571	0.000	0.400	0.364	0.000
sn4	6	5	0.364	0.308	0.000	0.267	0.400	0.000
sn5	6	6	0.400	0.500	0.000	0.250	0.364	0.000
sn6	6	10	0.414	0.387	0.400	0.343	0.480	0.286
sn7	6	12	0.429	0.476	0.430	0.353	0.316	0.267
sn8	7	6	0.571	0.667	0.000	0.444	0.381	0.000
sn9	7	7	0.267	0.588	0.000	0.545	0.444	0.222
sn10	7	7	0.364	0.286	0.000	0.462	0.400	0.000
sn11	7	7	0.250	0.364	0.000	0.286	0.286	0.000
sn12	7	8	0.462	0.667	0.500	0.286	0.308	0.333
sn13	7	9	0.381	0.677	0.133	0.364	0.636	0.000
sn14	7	11	0.250	0.594	0.267	0.250	0.500	0.250
sn15	7	11	0.361	0.411	0.361	0.250	0.316	0.200
sn16	7	14	0.320	0.333	0.222	0.258	0.308	0.207
sn17	9	12	0.222	0.444	0.125	0.325	0.522	0.154
sn18	9	16	0.293	0.404	0.190	0.299	0.333	0.167
sn19	10	17	0.174	0.286	0.182	0.195	0.289	0.195
sn20	11	13	0.214	0.778	0.148	0.200	0.568	0.105
sn21	12	23	0.216	0.250	0.108	0.205	0.321	0.212
sn22	13	38	0.226	0.210	0.195	0.180	0.252	0.183

Complete is D-CLINDE or GlobalMIT+ on the complete data. hidden is our proposed algorithm on the incomplete data (without the hidden node). ignoreHidden is D-CLINDE or GlobalMIT+ on the incomplete data.

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