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This value πmp is the possibility of the most possible flux distribution.
**Minimized sum of squared residuals, possibility of the most possible flux vector (P) and degree of measurements uncertainty to P = 1.
Two different analysis of consistency were performed: one based on minimized, variance-weighted sum of squared residuals and another one based on the possibility of the most possible flux state or vector.
The obtained flux vector v mp contains the most possible flux values compatible (consistent) with the model and the measurements.
The most possible flux vector being not fully possible (peak value not equal to 1) indicates that the measurements and the model are not in complete agreement.
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Finally, it will be shown how (linear) optimisation problems will be able to settle queries about the most possible fluxes, the possibility distributions, etc.
Then, an efficient optimization-based approach will be employed to query the most possible fluxes and their possibility distributions.
Instead, we follow a constraint-based modeling approach, in the sense that we do not attempt necessarily to predict the actual fluxes with precision, but rather to distinguish "most possible" from "impossible" flux states, based on a suitable definition of "possibility", a constraint-based model and the available measurements, which in most cases do not include isotopic data.
The simplest point-wise estimate is the minimum-cost flux vector resulting from (7), which contains the most possible value for each flux.
The 'uniform' nature of the sampling is based only on the mathematical description of the set of possible flux distributions, avoiding any prior assumption on which metabolic states are most likely to be selected in vivo.
Most possible modes.
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