Efficient reconstruction of biological networks via transitive reduction on general purpose graphics processors

BMC Bioinformatics

Table 3 Results with the networks of size 100 nodes from the DREAM4 benchmark

Network + reconstruction method	TP	TN	FP	FN	AUROC	AUPR
Network 1 (176 edges)
-perturbation graph	114	9467	257	62	0.8851	0.5138
-perturbation graph + Cutter-u	107	9532	192	69	0.8848	0.5082
-perturbation graph + Transwesd	108	9547	177	68	0.8854	0.5366
-perturbation graph + Cutter-w	109	9582	142	67	0.8857	0.5475
Network 2 (249 edges)
-perturbation graph	106	9389	262	143	0.7877	0.3577
-perturbation graph + Cutter-u	98	9411	240	151	0.7871	0.3455
-perturbation graph + Transwesd	92	9473	178	157	0.7874	0.3636
-perturbation graph + Cutter-w	85	9516	135	164	0.7874	0.3604
Network 3 (195 edges)
-perturbation graph	93	9446	259	102	0.8490	0.3353
-perturbation graph + Cutter-u	91	9451	254	104	0.8488	0.3313
-perturbation graph + Transwesd	90	9543	162	105	0.8495	0.3574
-perturbation graph + Cutter-w	89	9563	142	106	0.8496	0.3673
Network 4 (211 edges)
-perturbation graph	112	9403	286	99	0.8474	0.3932
-perturbation graph + Cutter-u	111	9418	271	100	0.8474	0.3938
-perturbation graph + Transwesd	101	9510	179	110	0.8478	0.4214
-perturbation graph + Cutter-w	96	9538	151	115	0.8477	0.4201
Network 5 (193 edges)
-perturbation graph	66	9230	477	127	0.7667	0.1580
-perturbation graph + Cutter-u	66	9230	477	127	0.7667	0.1580
-perturbation graph + Transwesd	56	9409	298	137	0.7665	0.1653
-perturbation graph + Cutter-w	52	9495	212	141	0.7666	0.1661

TP = true positives, TN = true negatives, FP = false positives, FN = false negatives. AUROC = area under the receiver-operator characteristics curve and AUPR = area under the precision-recall curve are computed by the Dream 4 evaluation scripts.

ISSN: 1471-2105