sysBiolAlg_lmoma-class: Class '"sysBiolAlg_lmoma"'

In sybil: Efficient Constrained Based Modelling

Description

The class sysBiolAlg_lmoma holds an object of class optObj which is generated to meet the requirements of a lineraized versoin of the MOMA algorithm.

Details

The initialize method has the following arguments:

model

An object of class modelorg.

wtflux

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, but solverParm is not.

COBRAflag

Boolean, prepare problem object in order to perform minimization of metabolic adjustment as in COBRA Toolbox.
Default: FALSE.

wtobj

Only used if argument COBRAflag is set to TRUE: A single numeric value giving the optimized value of the objective function of the wild type problem. If missing, a default value is computed based on FBA. If given, arguments solver and method are used, but solverParm is not.

wtobjLB

Only used if argument COBRAflag is set to TRUE: Boolean. If set to TRUE, the value of argument wtobj is treated as lower bound. If set to FALSE, wtobj serves as an upper bound.
Default: TRUE.

obj_coefD

A numeric vector of length two times the number of reactions in the model containing the non-zero part of the objective function. If set to NULL, the vector is filled with ones.
Default: NULL.

absMAX

A single numerical value used as a maximum value for upper variable and contraint bounds.
Default: SYBIL_SETTINGS("MAXIMUM").

useNames

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").

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 a linearized version of the MOMA algorithm with a given model, which is basically the solution of a linear programming problem

min sum |v_j,del - v_i,wt| for i,j = 1, ..., n s.t. Sv_del = 0 v_i = vi_i,wt for i = 1, ..., n a_j <= v_j,del <= b_j for j = 1, ..., n

Here, v_wt 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.

If argument COBRAflag is set to TRUE, the linear programm is formulated differently. Wild type and knock-out strain will be computed simultaneously.

min sum |v_j,del - v_i,wt| for i,j = 1, ..., n s.t. Sv_wt = 0 v_i = vi_i,wt for i = 1, ..., n Sv_del = 0 a_j <= v_j,del <= b_j for j = 1, ..., n mu_wt = c^T v_wt

with S being the stoichiometric matrix, a_i and b_i being the lower and upper bounds for flux (variable) i (j for the deletion strain). The total number of variables of the optimization problem is denoted by n. Here, mu_wt is the optimal wild type growth rate. This can be set via the argument wtobj. If wtobj is NULL (the default), the wild type growth rate will be calculated by a standard FBA. The optimization can be executed by using optimizeProb.

Objects from the Class

Objects can be created by calls of the form

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

Arguments to ... which are passed to method initialize of class sysBiolAlg_lmoma 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_lmoma" in the signature.

Author(s)

Gabriel Gelius-Dietrich <[e-mail]>

Maintainer: Mayo Roettger <[e-mail]>

References

Becker, S. A., Feist, A. M., Mo, M. L., Hannum, G., Palsson, B. Ø. and Herrgard, M. J. (2007) Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox. Nat Protoc 2, 727–738.

Edwards, J. S., Covert, M and Palsson, B. Ø. (2002) Metabolic modelling of microbes: the flux-balance approach. Environ Microbiol 4, 133–140.

Edwards, J. S., Ibarra, R. U. and Palsson, B. Ø. (2001) In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data. Nat Biotechnol 19, 125–130.

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.

Segrè, D., Vitkup, D. and Church, G. M. (2002) Analysis or optimality in natural and pertubed metabolic networks. PNAS 99, 15112–15117.

See Also

Constructor function sysBiolAlg and superclass sysBiolAlg.

Examples

  showClass("sysBiolAlg_lmoma")

sybil documentation built on May 31, 2021, 5:08 p.m.