R bindings for libSBML 5.5.0

R, an environment for statistical computing, enjoys popularity in the wider fields of computational biology. Until now, if you would feel like consuming an SBML model in R you could use the Bioconductor project rsbml. It would be great for reading SBML (by transforming it into a DOM).

Over the past weeks I’ve spend some time looking into R bindings for libSBML based on SWIG code generation. This will make it possible to fully create / manipulate / validate SBML documents from R. At the same time support for all SBML packages will be readily available.

First experiments seem to be quite convincing, I’ve ported all the C examples over to R (isn’t it nice how you can write C code in any language?). From here I would hope that some R and SBML enthusiast could write some helper functions to make the functions more R-like. Here the examples:

• addCVTerms.R
• addingEvidenceCodes_1.R
• addingEvidenceCodes_2.R
• addModelHistory.R
• appendAnnotation.R
• convertSBML.R
• createExampleSBML.R
• echoSBML.R
• evaluateMath.R
• printAnnotation.R
• printMath.R
• printNotes.R
• printRegisteredPackages.R
• printSBML.R
• printSupported.R
• printUnits.R
• readSBML.R
• translateMath.R
• unsetAnnotation.R
• unsetNotes.R
• validateSBML.R

In order to install the bindings you need to have R 2.15.1 simply download the binary package for your system:

• Win32 (universal)
• OSX (universal)
• Ubuntu 12 (32bit)
• Ubuntu 12 (64bit)

And then execute

R CMD INSTALL <archivename>

(or choose install from local package in the RGui.) I did not have luck renaming these files, so perhaps the names have to be what they are. If you are interested in compiling a binary package from source, you can use the CMake build files and select WITH_R to have it build the R bindings (tested with SWIG 2.0.4). In any case I would look forward to hear how it is working for you.