Description Details Objects from the Class Slots Extends Methods Note Author(s) References See Also Examples
The class sysBiolAlg_room holds an object of class
optObj which is generated to meet the
requirements of the ROOM algorithm.
The initialize method has the following arguments:
An object of class modelorg.
A numeric vector holding an optimal wild type flux distribution for the
given model. If missing, a default value is computed based on FBA.
If given, arguments solver and method are used to calculate
the dafault, but solverParm is not.
A single numeric value giving the relative range of tolerance, see
Details below.
Default: 0.03.
A single numeric value giving the absolute range of tolerance, see
Details below.
Default: 0.001.
Boolean. If TRUE, the problem object is formulated as linear
program. See Details below.
Default: FALSE.
Boolean. If TRUE, the problem object is formulated as linear
program. See Details below.
Default: FALSE.
A single numerical value used as a maximum value for upper variable
and contraint bounds.
Default: SYBIL_SETTINGS("MAXIMUM").
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 the ROOM algorithm with a given model, which is basically the solution of a mixed integer programming problem
max sum (v_j,del - v_i,wt)^2 for i,j = 1, ..., n s.t. Sv = 0 a_i <= v_i <= b_i for i = 1, ..., n
with S being the stoichiometric matrix, a_i
and b_i being the lower and upper bounds for flux (variable)
i.
The total number of fluxes of the optimization problem is denoted by n.
Here, w is the optimal wild type flux distribution. This can be set via
the argument wtflux. If wtflux is NULL (the default), the
wild type flux distribution will be calculated by a standard FBA.
All variables y_i are binary, with y_i = 1 for a significant flux
change in v_i and y_i = 0 otherwise. Thresholds determining the
significance of a flux change are given in w^u and w^l, with
delta and epsilon specifying absolute and
relative ranges in tolerance [Shlomi et al. 2005].
The Boolean argument LPvariant relax the binary contraints to
0 <= y_i <= 1 so that the problem becomes a linear
program.
The optimization can be executed by using optimizeProb.
Objects can be created by calls of the form
sysBiolAlg(model, algorithm = "room", ...).
Arguments to ... which are passed to method initialize of class
sysBiolAlg_room are described in the Details section.
wu:Object of class "numeric"
containing the upper threshold for a significant flux change,
see Details below.
wl:Object of class "numeric"
containing the lower threshold for a significant flux change,
see Details below.
fnc:Object of class "integer"
containing the number of reactions in the entire metabolic network
(argument model to the constructor function
sysBiolAlg).
fnr:Object of class "integer"
containing the number of metabolites in the entire metabolic network
(argument model to the constructor function
sysBiolAlg).
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.
Class "sysBiolAlg", directly.
signature(object = "sysBiolAlg_room"):
runs optimization on the given problem object
(see optimizeProb for details).
If using glpkAPI as MIP solver, consider to set parameter
PRESOLVE to GLP_ON.
Gabriel Gelius-Dietrich <geliudie@uni-duesseldorf.de>
Maintainer: Mayo Roettger <mayo.roettger@hhu.de>
Shlomi, T., Berkman, O. and Ruppin, E. (2005) Regulatory on/off minimization of metabolic flux changes after genetic pertubations. PNAS 102, 7695–7700.
Constructor function sysBiolAlg and
superclass sysBiolAlg.
1 | showClass("sysBiolAlg_room")
|
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