. 2011 Nov 3;12:430. doi: 10.1186/1471-2105-12-430

Table 3.

Evaluation of different methods using HMR195 and BG570 genomic datasets.

	BG570							HMR195

		S_n							S_n

		%10		%30		%50			%10		%30		%50

Methods	AUC	FP	S_p	FP	S_p	FP	S_p	AUC	FP	S_p	FP	S_p	FP	S_p
DFT	0.6540	279	45.8	767	43.3	1412	34.3	0.6782	438	51.5	1184	45	2064	41.7
AN filter	0.6765	121	55	499	49.7	1103	36.7	0.7615	151	64.4	526	57.4	1217	51.1
Asif	0.5748	140	34.2	330	31.7	554	29.1	0.6261	214	47.1	473	44.6	787	39.9
AMDF	0.6600	340	40.8	770	39.4	1309	35.3	0.6980	410	47.9	1010	46.8	1821	43.3
TDP	0.7560	160	62	408	56	805	49.4	0.7850	262	64.8	627	60.4	1128	56
Cross-correlation (proposed)	0.8143	81	75.5	244	69	547	61	0.8250	124	71	382	67	841	59

Table 3 shows the area under the ROC curve (AUC), the number of false positives (FP), the approximate correlation (AC) and specificity (S_p) at a given sensitivity (S_n) for the proposed method and for other methods using the BG570 and HMR195 datasets.