sybil – Efficient Constraint Based Modelling in R

The package sybil is a Systems Biology Library for undefinedGNU R, implementing algorithms for constraint based analysis of metabolic networks. Among other functions, sybil currently provides efficient methods for flux-balance analysis (FBA), minimization of metabolic adjustment (MOMA), regulatory on/off minimization (ROOM), flux variability Analysis and robustness Analysis. Sybil makes use of the sparse matrix implementation in the R-package undefinedMatrix.

Download

Sybil is available for download on undefinedCRAN.

Features

  • flux-balance analysis (FBA)
  • minimization of metabolic adjustment (MOMA)
  • regulatory on/off minimization (ROOM)
  • simulate gene knock-outs (single, double, n)
  • flux variability analysis
  • robustness analysis
  • read undefinedSBML formatted files
  • read output from undefinedBiGG database
  • interfaceing mathematical programming software: undefinedGLPK, undefinedCOIN-OR Clp, undefinedIBM ILOG CPLEX, undefinedlp_solve and undefinedGurobi
  • set or change all parameters provided by the mathematical programming software
  • extendable with new algorithms due to object oriented programming interface

Citation

To cite package sybil in publications use:

Gelius-Dietrich, G., Amer Desouki, A., Fritzemeier, C.J. and Lercher, M.J. “sybil – Efficient constraint-based modelling in R”. BMC Systems Biology, 2013. 7:125.

doi:10.1186/1752-0509-7-125

Article: undefinedhttp://www.biomedcentral.com/1752-0509/7/125

Additional Packages

sybilSBML

The package sybilSBML (download on undefinedCRAN) is an extension to sybil in order to read undefinedSBML formatted files.

sybilGUROBI

The R-package sybilGUROBI makes the R-interface of undefinedGurobi available to sybil.


All packages are compatible with R version 2.15.3.

Sybil, sybilSBML and sybilGUROBI are non-profit projects. They are published under the GNU General Public License (GPL 3).

Contact: undefinedJonathan Fritzemeier

Example session in sybil

sybil session

Click on the image to see a larger version.

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