A specialized learner for inferring structured cis-regulatory modules

BMC Bioinformatics

Table 4 Results

	Data set	True Positives	False Positives	True Negatives	False Negatives	Precision	Recall	F1 Score	p-value
Lee et al.	GAT3, RGM1	5	22	78	10	0.185	0.333	0.238	0.253
	GAL4, YAP5	7	16	84	9	0.304	0.438	0.359	0.0169
	GAT3, PDR1	10	9	91	7	0.526	0.588	0.556	1.138e-05
	CIN5, NRG1	10	18	82	8	0.357	0.556	0.435	1.53e-03
	RGM1, YAP5	7	13	87	11	0.35	0.389	0.368	0.0137
	NDD1, SWI4	15	23	77	7	0.395	0.682	0.5	8.51e-05
	SKN7, SWI4	12	38	62	10	0.24	0.545	0.333	0.118
	PDR1, YAP5	13	36	64	10	0.265	0.565	0.361	0.0585
	FKH2, SWI4	11	20	80	13	0.355	0.458	0.4	0.0113
	PHD1, YAP6	14	18	82	10	0.438	0.583	0.5	1.52-e04
	FHL1, YAP5	15	19	81	10	0.441	0.6	0.508	1.07-e04
	FKH2, MCM1	20	33	67	5	0.377	0.8	0.513	2.45-e05
	MBP1, NDD1	13	24	76	12	0.351	0.52	0.419	7.52-e03
	ACE2, SWI5	17	29	71	9	0.37	0.654	0.472	7.97-e04
	FKH2, MBP1	19	31	69	8	0.38	0.704	0.494	2.60-e04
	MCM1, NDD1	24	36	64	4	0.4	0.857	0.545	2.37-e06
	RAP1, YAP5	15	7	93	14	0.682	0.517	0.588	3.68-e07
	NRG1, YAP6	15	22	78	15	0.405	0.5	0.448	3.72-e03
	GAT3, YAP5	25	11	89	14	0.694	0.641	0.667	8.75-e10
	CIN5, YAP6	26	41	59	14	0.388	0.65	0.486	8.47-e03
	MBP1, SWI4	27	33	67	13	0.45	0.675	0.54	2.00-e04
	SWI4, SWI6	20	45	55	23	0.308	0.465	0.37	0.506
	MBP1, SWI6	39	38	62	5	0.506	0.886	0.645	6.34-e09
	FKH2, NDD1	35	83	17	15	0.297	0.7	0.417	0.978
	FHL1, RAP1	89	36	64	25	0.712	0.781	0.745	3.33-e10
Gasch et al.	iESR	89	453	4497	181	0.164	0.33	0.219	~0
	rESR_PACcluster	173	260	4690	255	0.4	0.404	0.402	~0
	rESR_RPcluster	50	84	4866	71	0.373	0.413	0.392	~0
Sinha et al.	Yeast	6	2	7	0	0.75	1	0.857	5.59-e03
Sinha et al.	Fly	3	3	97	5	0.5	0.375	0.429	4.92-e03
Sinha et al.	Fly, known PWMs	7	10	90	1	0.412	0.875	0.560	5.10e-06

Results of running our algorithm on the data in Table 3. Significant CRMs (p-value < 0.01) are indicated with bold text.

ISSN: 1471-2105