Table 2.
Elements and the statistical indices for multiple linear regression models which link the values of metabolic fluxes and the average AA property for the yeast Saccharomyces cerevisiae enzyme sequences, expressed according to the VARIMAX scales.
| Model | Dependenta
variable |
Parametersb | Regression coefficient (standardized value) |
S.E. | t value | P value |
R
2, % R adj. 2, % |
VIFc |
|---|---|---|---|---|---|---|---|---|
| I | Metabolic flux (Teusink's model) | Constant | 142.527 | 3.150 | 45.25 | 0.0000 | 94.46 | |
| 93.32 | ||||||||
| P aveWV7 | 1749.250 (1.141) | 80.843 | 21.64 | 0.0000 | 1.71 | |||
| P aveWV5 | −1347.310 (−0.948) | 86.853 | −15.51 | 0.0000 | 2.29 | |||
| (P aveWV1)2 | −1234.03 (−0.540) | 124.491 | −9.91 | 0.0000 | 1.82 | |||
| (P aveWV5)2 | −11296.70 (−0.310) | 1930.380 | −5.85 | 0.0000 | 1.73 | |||
| (P aveWV2)2 | −6350.430 (−0.289) | 1137.530 | −5.58 | 0.0000 | 1.64 | |||
| P aveWV6 | 202.670 (0.222) | 48.639 | 4.17 | 0.0002 | 1.74 | |||
| P aveWV1 | 44.481 (0.125) | 17.534 | 2.54 | 0.0159 | 1.50 | |||
|
| ||||||||
| II | Metabolic flux (Hynne's model) | Constant | 70.629 | 3.394 | 20.81 | 0.0000 | 94.20 | |
| 92.91 | ||||||||
| (P aveWV2)2 | −0.780 (−0.638) | 0.081 | −9.65 | 0.0000 | 2.71 | |||
| P aveWV7 | 8.965 (1.028) | 0.575 | 15.60 | 0.0000 | 2.70 | |||
| P aveWV1 | −0.836 (−0.396) | 0.112 | −7.47 | 0.0000 | 1.74 | |||
| (P aveWV1)2 | −0.083 (−0.610) | 0.008 | −10.11 | 0.0000 | 2.26 | |||
| (P aveWV5)2 | −0.787 (−0.618) | 0.076 | −10.31 | 0.0000 | 2.23 | |||
| P aveWV5 | −3.874 (−0.581) | 0.383 | −10.11 | 0.0000 | 2.05 | |||
| P aveWV6 | 2.683 (0.505) | 0.311 | 8.63 | 0.0000 | 2.12 | |||
| (P aveWV3)2 | −0.085 (−0.414) | 0.014 | −5.97 | 0.0000 | 2.99 | |||
aRepresent the mean values of metabolic fluxes within the range of external glucose concentrations as specified in the “Material and Methods”.
bElements of multiple linear regression which represent the average AA property, as specified in the Table 1, of the yeast Saccharomyces cerevisiae enzyme sequences and the constant (intercept) of equation.
cThe variance inflation factor which indicates the impact of collinearity between the independent variables [22].