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We use several machine-learning tools in order to estimate enzyme activity and reaction efficiency at each step of the identified pathways.
We have developed a decision tree learning method to estimate enzyme activity [ 53] using kinetics information from the BRENDA database [ 54] (turnover rates, Michaelis constant K M, and inhibition constant K i).
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Recent studies have suggested that it may also be useful for estimating enzyme activities, however this potential has not been explored in detail.
The optimum pH of the enzyme was determined by estimating enzyme activities at 65 °C in 50 mM citrate phosphate buffer at different pH values (2.5 6.0).
Based on the kinetic parameters (maximum reaction rate and Michaelis constant) estimated, the enzyme activity was found to be effectively maintained under reduced pressure.
To further estimate antioxidant enzyme activities, the relative activities of CAT, SOD, and POD [ 35] in WT and TaNAC29-overexpression lines were measured at different time points following stress treatments.
To estimate the enzyme activities, fluorimetric GUS assays and NPTII ELISAs were performed on leaf samples from all of the plants every 3 months over a period of one year (2007).
Additional file 1: This file includes a list of substrates used in estimating cytochrome P450 enzyme activity.
By itself, then, A TA 7TAA does not reduce transcriptional activity to 42-50%, which is the value estimated from the enzyme activity and the amount of enzyme protein in human liver samples of homozygous A TA 7TAA [ 18- 20].
These parameters are used to estimate the effects of enzyme activity increases and decreases on the corresponding reaction flux capacity distributions.
The quality of the match to the actual measured gene expression values was calculated with the observed gene expression assumed to be proportional to enzyme expression and taken as a direct estimate of the observed enzyme activity Eobs.
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