BMC Bioinformatics

Table 4 The number of drugs inside and outside of the AD

From: Prediction of the effects of small molecules on the gut microbiome using machine learning method integrating with optimal molecular features

		Inside		Outside		AD coverage (%)
		P	N	P	N	AD coverage (%)
1	Training set	301	637	4	5	99.0
1	External validation set	86	148	0	2	99.2
2	Training set	297	639	4	5	99.0
2	External validation set	90	144	0	2	99.2
3	Training set	329	607	4	5	99.0
3	External validation set	58	177	0	1	99.6
4	Training set	304	632	4	5	99.0
4	External validation set	82	153	1	0	99.6
5	Training set	333	603	4	5	99.0
5	External validation set	54	181	0	1	99.6
6	Training set	311	625	4	5	99.0
6	External validation set	76	159	0	1	99.6
7	Training set	315	621	2	7	99.0
7	External validation set	72	159	2	3	97.9
8	Training set	316	620	3	6	99.0
8	External validation set	69	159	3	5	96.6
9	Training set	315	621	5	4	99.0
9	External validation set	71	164	0	1	99.6
10	Training set	337	599	3	6	99.0
10	External validation set	50	183	1	2	98.7
11	Training set	311	625	4	5	99.0
11	External validation set	75	156	1	4	97.9
12	Training set	305	631	3	6	99.0
12	External validation set	81	152	2	1	98.7
13	Training set	319	617	3	6	99.0
13	External validation set	68	165	1	2	98.7
14	Training set	325	611	4	5	99.0
14	External validation set	62	174	0	0	100
15	Training set	319	617	3	6	99.0
15	External validation set	68	167	1	0	99.6
16	Training set	315	621	3	6	99.0
16	External validation set	72	160	1	3	98.3
17	Training set	316	620	3	6	99.0
17	External validation set	72	162	0	2	99.2
18	Training set	312	624	4	5	99.0
18	External validation set	74	159	1	2	98.7

Back to article page

ISSN: 1471-2105

Contact us

General enquiries: journalsubmissions@springernature.com