sybil (version 2.2.0)

sybil-package: sybil -- Efficient Constrained Based Modelling in R

Description

The package sybil is a collection of functions designed for in silico analysis---in particular constrained based analysis---of metabolic networks.

Details

The package sybil is designed to read metabolic networks from csv files. This is done by the function readTSVmod. The function returns an object of the class '>modelorg.

Read csv files (example files included):

mpath <- system.file(package = "sybil", "extdata")
model <- readTSVmod(prefix = "Ec_core",
                    fpath = mpath, quote = "\"")
  

Perform flux balance analysis (FBA): ec_f <- optimizeProb(model)

Perform single gene deletion analysis: ec_g <- oneGeneDel(model)

Plot the values of the objective function after optimization in a histogram: plot(ec_g)

Perform flux variability analysis: ec_v <- fluxVar(model)

Plot the result: plot(ec_v)

References

Gelius-Dietrich, G., Desouki, A. A., Fritzemeier, C. J., and Lercher, M. J. (2013). sybil -- Efficient constraint-based modelling in R. BMC Systems Biology 7, 125.

The BiGG database http://bigg.ucsd.edu/.

Schellenberger, J., Park, J. O., Conrad, T. C., and Palsson, B. <U+00D8>., (2010) BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions. BMC Bioinformatics 11, 213.

The openCOBRA project https://opencobra.github.io/.

Becker, S. A., Feist, A. M., Mo, M. L., Hannum, G., Palsson, B. <U+00D8>. and Herrgard, M. J. (2007) Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox. Nat Protoc 2, 727--738.

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. <U+00D8>. (2011) Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0. Nat Protoc 6, 1290--1307.

See Also

Package sybilSBML and there the function readSBMLmod to read metabolic models written in SBML language.

Examples

# NOT RUN {
  data(Ec_core)
  Ec_ofd <- oneGeneDel(Ec_core)
  plot(Ec_ofd)
# }