Sybil--efficient constraint-based modelling in R.
BACKGROUND
Constraint-based analyses of metabolic networks are widely used to simulate the properties of genome-scale metabolic networks. Publicly available implementations tend to be slow, impeding large scale analyses such as the genome-wide computation of pairwise gene knock-outs, or the automated search for model improvements. Furthermore, available implementations cannot easily be extended or adapted by users.


RESULTS
Here, we present sybil, an open source software library for constraint-based analyses in R; R is a free, platform-independent environment for statistical computing and graphics that is widely used in bioinformatics. Among other functions, sybil currently provides efficient methods for flux-balance analysis (FBA), MOMA, and ROOM that are about ten times faster than previous implementations when calculating the effect of whole-genome single gene deletions in silico on a complete E. coli metabolic model.


CONCLUSIONS
Due to the object-oriented architecture of sybil, users can easily build analysis pipelines in R or even implement their own constraint-based algorithms. Based on its highly efficient communication with different mathematical optimisation programs, sybil facilitates the exploration of high-dimensional optimisation problems on small time scales. Sybil and all its dependencies are open source. Sybil and its documentation are available for download from the comprehensive R archive network (CRAN).
Gabriel
G
Gelius-Dietrich
Abdelmoneim Amer
AA
Desouki
Claus Jonathan
CJ
Fritzemeier
Institute for Computer Science, Heinrich-Heine-University, Universitätsstr 1, 40225 Düsseldorf, Germany. lercher@cs.uni-duesseldorf.de.
Martin J
MJ
Lercher
D019295:Computational Biology / Q000379:methods*; D003196:Computer Graphics; D003198:Computer Simulation; D004926:Escherichia coli / Q000378:metabolism; D008954:Models, Biological; D011381:Programming Languages