A principal components method constrained by elementary flux modes: analysis of flux data sets

BMC Bioinformatics

Table 4 Selected EMs and the respective captured variance (ϑ) values for one to ten number of n _Facs obtained for experimental data extracted from [28] and [29]

n _Fac	EM/ϑ	1	2	3	4	5	6	7	8	9	10	11	12	13
1	EMs	915
1	ϑ	28.12
2	EMs	915	1145
2	ϑ	28.12	46.44
3	EMs	678	1145	988
3	ϑ	25.54	44.93	56.05
4	EMs	1145	663	968	750
4	ϑ	22.62	41.62	55.31	65.07
5	EMs	1145	663	968	750	48
5	ϑ	22.62	41.62	55.31	65.07	72.62
6	EMs	1145	663	968	750	48	31
6	ϑ	22.62	41.62	55.31	65.07	72.62	77.23
7	EMs	1145	663	766	968	48	31	1047
7	ϑ	22.62	41.62	55.33	65.05	72.61	77.22	81.15
8	EMs	1145	663	750	48	647	718	31	1040
8	ϑ	22.62	41.62	55.25	62.80	69.99	76.42	81.03	84.98
9	EMs	1145	663	750	48	647	718	31	1040	641
9	ϑ	22.62	41.62	55.25	62.80	69.99	76.42	81.03	84.98	87.61
10	EMs	1145	972	697	750	48	685	31	999	659	501
10	ϑ	22.62	40.25	51.57	62.43	69.99	75.60	80.21	83.94	87.57	90.20
PCA	#Lv	1	2	3	4	5	6
PCA	n_lv**	68.44	84.28	94.82	98.42	99.53	100.00
BF*	EMs	893	1123	675	1115	26	13	1022	637	630	672	33	1155	1117
BF*	ϑ	28.12	46.44	55.71	64.85	72.40	77.01	80.69	84.14	86.77	89.19	90.42	91.29	91.73

n _lv ** number of latent variables for PCA. BF* best first solution obtained by the greedy approach

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