recipe bioconductor-rsbml

R support for SBML, using libsbml






Links R to libsbml for SBML parsing, validating output, provides an S4 SBML DOM, converts SBML to R graph objects. Optionally links to the SBML ODE Solver Library (SOSLib) for simulating models.

package bioconductor-rsbml

(downloads) docker_bioconductor-rsbml



depends bioconductor-biocgenerics:


depends bioconductor-biocgenerics:


depends bioconductor-graph:


depends bioconductor-graph:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends libsbml:


depends libsbml:


depends libstdcxx-ng:


depends r-base:




You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-rsbml

and update with::

   mamba update bioconductor-rsbml

To create a new environment, run:

mamba create --name myenvname bioconductor-rsbml

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull<tag>

(see `bioconductor-rsbml/tags`_ for valid values for ``<tag>``)

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