recipe bioconductor-cellnoptr

Training of boolean logic models of signalling networks using prior knowledge networks and perturbation data







biotools: cellnoptr, doi: 10.1186/1752-0509-6-133

This package does optimisation of boolean logic networks of signalling pathways based on a previous knowledge network and a set of data upon perturbation of the nodes in the network.

package bioconductor-cellnoptr

(downloads) docker_bioconductor-cellnoptr



depends bioconductor-graph:


depends bioconductor-graph:


depends bioconductor-rbgl:


depends bioconductor-rbgl:


depends bioconductor-rgraphviz:


depends bioconductor-rgraphviz:


depends graphviz:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends r-base:


depends r-ggplot2:

depends r-igraph:

depends r-rcurl:

depends r-rmarkdown:

depends r-stringi:

depends r-stringr:

depends r-xml:



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-cellnoptr

and update with::

   mamba update bioconductor-cellnoptr

To create a new environment, run:

mamba create --name myenvname bioconductor-cellnoptr

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-cellnoptr/tags`_ for valid values for ``<tag>``)

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