"sysBiolAlg_fv"sysBiolAlg_fv holds an object of class
optObj which is generated to meet the
requirements of the flux variance algorithm.sysBiolAlg(model, algorithm = "fv", ...).
Arguments to ... which are passed to method initialize of class
sysBiolAlg_fv are described in the Details section."sysBiolAlg ", directly.initialize method has the following arguments:
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object] The problem object is built to be capable to perform the flux variance
algorithm with a given model, which is basically the solution of a linear
program
$$\begin{array}{rll} \max \textrm{ or } \min & v_i \[1ex]
\mathrm{s.\,t.} & Z = Z_{\mathrm{opt}} \[1ex]
& \mbox{\boldmath$Sv$\unboldmath} = 0 \[1ex]
& \alpha_i \leq v_i \leq \beta_i
& \quad \forall i \in {1, \ldots, n} \[1ex]
\end{array}$$
with $\bold{S}$ beeing the stoichiometric matrix, $\alpha_i$
and $\beta_i$ beeing the lower and upper bounds for flux (variable)
$i$. The total number of variables of the optimization problem is denoted
by $n$.
The optimization can be executed by using optimizeProb.
Schellenberger, J., Que, R., Fleming, R. M. T., Thiele, I., Orth, J. D., Feist, A. M., Zielinski, D. C., Bordbar, A., Lewis, N. E., Rahmanian, S., Kang, J., Hyduke, D. R. and Palsson, B. Ø. (2011) Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0. Nat Protoc 6, 1290--1307.
Bernhard Ø. Palsson (2006). Systems Biology: Properties of Reconstructed Networks. Cambridge University Press.
sysBiolAlg and
superclass sysBiolAlg.