"sysBiolAlg_mtf"
The class sysBiolAlg_mtf
holds an object of class
'>optObj
which is generated to meet the
requirements of the minimize total flux algorithm: minimize the absolute sum
of all fluxes given a previously calculated objective value.
Objects can be created by calls of the form
sysBiolAlg(model, algorithm = "mtf", ...)
.
Arguments to ...
which are passed to method initialize
of class
sysBiolAlg_mtf
are described in the Details section.
maxobj
:Object of class "numeric"
containing optimized objective values.
problem
:Object of class "optObj"
containing the problem object.
algorithm
:Object of class "character"
containing the name of the algorithm.
nr
:Object of class "integer"
containing the number of rows of the problem object.
nc
:Object of class "integer"
containing the number of columns of the problem object
fldind
:Object of class "integer"
pointers to columns (variables) representing a flux (reaction) in the
original network. The variable fldind[i]
in the problem object
represents reaction i
in the original network.
alg_par
:Object of class "list"
containing a named list containing algorithm specific parameters.
signature(object = "sysBiolAlg_mtf")
:
change current objective value to the \(j\)th value given in slot
maxobj
. Argument j
must be in [1:length(maxobj)]
.
The initialize
method has the following arguments:
A single numeric value giving the optimal value. If missing, a default
value is computed based on FBA. If given, arguments solver
and
method
are used, but solverParm
is not.
Default: NULL
.
Arguments react
, lb
and ub
are used, if argument
wtobj
is NULL
, meaning: no previous objective value is
given. Objective values will be calculated via fba
using
the parameters given in react
, lb
and ub
.
Default: NULL
.
See argument react
.
Default: NULL
.
See argument react
.
Default: NULL
.
A numeric vector containing cost coefficients for all variables (forward
direction). If set to NULL
, all cost coefficients are set to
1
, so that all variables have the same impact on the objective
function.
Default: NULL
.
A numeric vector containing cost coefficients for all variables (backward
direction). If set to NULL
, all cost coefficients are set to the
values given in costcoeffw
.
Default: NULL
.
A single numerical value used as a maximum value for upper variable
and contraint bounds.
Default: SYBIL_SETTINGS("MAXIMUM")
.
A single boolean value. If set to TRUE
, variables and constraints
will be named according to cnames
and rnames
. If set to
NULL
, no specific variable or constraint names are set.
Default: SYBIL_SETTINGS("USE_NAMES")
.
A character vector giving the variable names. If set to NULL
,
the reaction id's of model
are used.
Default: NULL
.
A character vector giving the constraint names. If set to NULL
,
the metabolite id's of model
are used.
Default: NULL
.
A single character string containing a name for the problem object.
Default: NULL
.
Scaling options used to scale the constraint matrix. If set to
NULL
, no scaling will be performed
(see scaleProb
).
Default: NULL
.
A single character string containing a file name to which the problem
object will be written in LP file format.
Default: NULL
.
Further arguments passed to the initialize method of
'>sysBiolAlg
. They are solver
,
method
and solverParm
.
The problem object is built to be capable to perform minimize total flux
with a given model, which is basically the solution of a linear programming
problem
$$%
\begin{array}{rll}%
\min & \begin{minipage}[b]{2.5em}
\[
\sum_{i=1}^n cost_i |v_i|
\]
\end{minipage} \\[2em]
\mathrm{s.\,t.} & \mbox{\boldmath$Sv$\unboldmath} = 0 \\[1ex]
& \alpha_i \leq v_i \leq \beta_i
& \quad \forall i \in \{1, \ldots, n\} \\[1ex]
& \mbox{\boldmath$c$\unboldmath}_{\mathrm{wt}} \geq
\mbox{\boldmath$c$\unboldmath}^{\mathrm{T}}
\mbox{\boldmath$v$\unboldmath}_{\mathrm{wt}} \\[1ex]
\end{array}%
$$
with
\(
\mbox{\boldmath$c$\unboldmath}^{\mathrm{T}}
\mbox{\boldmath$v$\unboldmath}_{\mathrm{wt}}
\)
being the previously computed optimized value of the objective function
(argument wtobj
).
The variable \(\bold{S}\) denotes the stoichiometric matrix,
\(\alpha_i\) and \(\beta_i\) being 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
.
Edwards, J. S., Covert, M and Palsson, B. <U+00D8>. (2002) Metabolic modelling of microbes: the flux-balance approach. Environ Microbiol 4, 133--140.
Edwards, J. S., Ibarra, R. U. and Palsson, B. <U+00D8>. (2001) In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data. Nat Biotechnol 19, 125--130.
Constructor function sysBiolAlg
and
superclass '>sysBiolAlg
.
# NOT RUN {
showClass("sysBiolAlg_mtf")
# }
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