sysBiolAlg_ccFBA-class: Class '"sysBiolAlg_ccFBA"'

In sybilccFBA: Cost Constrained Flux Balance Analysis (ccFBA): MetabOlic Modeling with ENzyme kineTics (MOMENT)

Description

The class sysBiolAlg_ccFBA holds an object of class optObj which is generated to meet the requirements of the ccFBA algorithm.

Details

The initialize method has the following arguments:

model

An object of class modelorg.

lpdir

Single character string containing the direction of optimization. Can be set to "min" or "max".
Default: "max".

LHS

constraint matrix, consists of S matrix and ccFBA constraints

rlb,rub

bounds for constraints (i.e rows)

lb,ub

bounds for variables (i.e columns)

rtype

row constraint type

obj

index of objective

cnames

A character vector giving the variable names. If set to NULL, the reaction id's of model are used.
Default: NULL.

rnames

A character vector giving the constraint names. If set to NULL, the metabolite id's of model are used.
Default: NULL.

pname

A single character string containing a name for the problem object.
Default: NULL.

scaling

Scaling options used to scale the constraint matrix. If set to NULL, no scaling will be performed (see scaleProb).
Default: NULL.

writeProbToFileName

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 cost constraint flux balance analysis (FBA) with a given model, which is basically the solution of a linear programming problem

max c^T v 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 respectively. The total number of variables of the optimization problem is denoted by n. The solution of the optimization is a flux distribution maximizing the objective function c^T v under the a given environment and the assumption of steady state. The optimization can be executed by using optimizeProb.

Objects from the Class

Objects can be created by calls of the form

sysBiolAlg(model, algorithm = "ccFBA", ...).

Arguments to ... which are passed to method initialize of class sysBiolAlg_ccFBA are described in the Details section.

Slots

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.

Extends

Class "sysBiolAlg", directly.

Methods

No methods defined with class "sysBiolAlg_ccFBA" in the signature.

Author(s)

Abdelmoneim Amer Desouki

References

Adadi, R., Volkmer, B., Milo, R., Heinemann, M., & Shlomi, T. (2012). Prediction of Microbial Growth Rate versus Biomass Yield by a Metabolic Network with Kinetic Parameters, 8(7). doi:10.1371/journal.pcbi.1002575

Gelius-Dietrich, G., Desouki, A. A., Fritzemeier, C. J., & Lercher, M. J. (2013). sybil–Efficient constraint-based modelling in R. BMC systems biology, 7(1), 125.

See Also

Constructor function sysBiolAlg and superclass sysBiolAlg.

sybilccFBA documentation built on Dec. 16, 2019, 1:34 a.m.