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Table 1 GenDev Technique A: Results for 2400 computational experiments using the General Development Mode (GenDev) with each biomass metabolite as an independent part of the objective function, that is, no constraint is applied to the overall biomass reaction

From: Evaluation of reaction gap-filling accuracy by randomization

(1) # rxns removed

1

2

5

10

20

50

(2) Rxns suggested are identical to rxns removed

48

na

22

na

3

na

0

na

0

na

0

na

 

52

50

22

23

3

7

0

0

0

0

0

0

(3) No rxns suggested

36

na

15

na

0

na

0

na

0

na

0

na

 

36

25

17

13

1

0

0

0

0

0

0

0

(4) Rxns suggested are a strict subset of rxns removed

0

na

40

na

43

na

27

na

8

na

0

na

 

0

0

42

35

40

7

21

36

9

23

0

4

(5) # rxns suggested is equal to # rxns re-moved

11

na

9

na

11

na

4

na

0

na

0

na

 

9

18

8

20

13

51

7

4

2

0

0

0

(6) # rxns suggested is less than # rxns re-moved

0

na

8

na

40

na

64

na

91

na

98

na

 

0

0

9

5

37

6

63

60

89

77

99

96

(7) # rxns suggested is greater than # rxns removed

5

na

6

na

3

na

5

na

1

na

0

na

 

3

7

2

4

6

33

9

0

0

0

0

0

(8) # cases where no solution was found

0

na

0

na

0

na

0

na

0

na

2

na

 

0

0

0

0

0

3

0

0

0

0

1

0

Precision (%)

77

na

81

na

79

na

80

na

79

na

77

na

 

83

69

83

78

75

84

79

85

79

89

76

89

Average precision (%)

     

79

na

     
      

79

82

     

Recall (%)

52

na

51

na

54

na

52

na

52

na

52

na

 

54

54

48

51

50

59

57

57

57

59

57

59

Average recall (%)

     

52

na

     
      

54

56

     
     

193 (32%)

na

    
     

223 (37%)

144 (24%)

    
  1. A GenDev solution is a set of suggested reactions to add to a degraded model to obtain growth. Each cell of this table is a 2x2 matrix whose first row is for the SCIP solver; the second row is for the CPLEX solver; the first column is for the Big M method; the second column is for the indicators method. For example, the cell on the first row and first column, has a matrix with value 48, which corresponds to SCIP using the Big M method, whereas the value 52 is for CPLEX (using the same method) and the value 50 is for CPLEX using indicators. A result “na” (not available) applies to SCIP using indicators — in most cases that solver could not find a solution in less than 30 min of computation. Each column of the table represents 400 computational experiments based on randomly removing the same number of active reactions from a base model (in each cell of the table, 100 experiments were run for each of the four cells in the matrix). The first row “# rxns Removed” lists the number of active reactions randomly removed. The other rows divide the 100 cases in each column into solutions of different types; for each cell of the small matrices, rows 2-8 of every column sum to 100. The best numbers are in bold, which could be the maximum or the minimum value depending on the row