recipe bioconductor-bnem

Training of logical models from indirect measurements of perturbation experiments






bnem combines the use of indirect measurements of Nested Effects Models (package mnem) with the Boolean networks of CellNOptR. Perturbation experiments of signalling nodes in cells are analysed for their effect on the global gene expression profile. Those profiles give evidence for the Boolean regulation of down-stream nodes in the network, e.g., whether two parents activate their child independently (OR-gate) or jointly (AND-gate).

package bioconductor-bnem

(downloads) docker_bioconductor-bnem



depends bioconductor-affy:


depends bioconductor-biobase:


depends bioconductor-cellnoptr:


depends bioconductor-epinem:


depends bioconductor-graph:


depends bioconductor-limma:


depends bioconductor-mnem:


depends bioconductor-rgraphviz:


depends bioconductor-sva:


depends bioconductor-vsn:


depends r-base:


depends r-binom:

depends r-cluster:

depends r-flexclust:

depends r-matrixstats:

depends r-rcolorbrewer:

depends r-rmarkdown:

depends r-snowfall:



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-bnem

and update with::

   mamba update bioconductor-bnem

To create a new environment, run:

mamba create --name myenvname bioconductor-bnem

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

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