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Table 1 Selected EMs and the respective captured variance (Ï‘) values for one to 10 number of n Fac s obtained for the simulated data without noise

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

n Fac

EM/Ï‘

1

2

3

4

5

6

7

8

9

10

1

EM

70

         

1

Ï‘

29.45

         

2

EMs

70

7

        

2

Ï‘

29.45

53.82

        

3

EMs

70

7

40

       

3

Ï‘

29.45

53.82

71.16

       

4

EMs

7

69

13

40

      

4

Ï‘

24.49

46.86

65.83

83.55

      

5

EMs

7

71

13

33

37

     

5

Ï‘

24.49

45.99

64.42

82.48

93.96

     

6

EMs

7

33

13

3

37

23

    

6

Ï‘

24.49

44.02

62.29

78.93

91.37

97.08

    

7

EMs

7

33

13

3

37

23

12

   

7

Ï‘

24.49

44.02

62.29

78.93

91.37

97.08

97.23

   

8

EMs

7

33

13

3

37

23

12

19

  

8

Ï‘

24.49

44.02

62.29

78.93

91.37

97.08

97.23

97.26

  

9

EMs

7

33

13

3

37

23

12

19

16

 

9

Ï‘

24.49

44.02

62.29

78.93

91.37

97.08

97.23

97.26

97.28

 

10

EMs

7

33

13

3

37

23

12

19

16

17

10

Ï‘

24.49

44.02

62.29

78.93

91.37

97.08

97.23

97.26

97.28

97.28

PCA

nlv**

1

2

3

4

5

6

7

8

9

 

PCA

Ï‘

50.16

82.19

91.85

97.00

99.27

99.96

100.00

100.00

100.00

 

BF*

EMs

70

7

40

13

37

23

14

12

8

16

BF*

Ï‘

29.45

53.82

71.16

82.44

90.54

91.84

92.04

92.12

92.17

92.20

  1. The set of truly active EMs for data generation was EMs = [1, 3, 7, 12, 13, 14, 16, 19, 20, 22, 23, 24, 28, 32, 33, 37]. BF* best-first identification by the greedy approach. n lv ** number of latent variables for PCA