recipe bioconductor-chemminer

Cheminformatics Toolkit for R







biotools: chemminer

ChemmineR is a cheminformatics package for analyzing drug-like small molecule data in R. Its latest version contains functions for efficient processing of large numbers of molecules, physicochemical/structural property predictions, structural similarity searching, classification and clustering of compound libraries with a wide spectrum of algorithms. In addition, it offers visualization functions for compound clustering results and chemical structures.

package bioconductor-chemminer

(downloads) docker_bioconductor-chemminer



depends bioconductor-biocgenerics:


depends bioconductor-biocgenerics:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-base:


depends r-base64enc:

depends r-bh:

depends r-dbi:

depends r-digest:

depends r-dt:

depends r-ggplot2:

depends r-gridextra:

depends r-jsonlite:

depends r-png:

depends r-rcpp:


depends r-rcurl:

depends r-rjson:

depends r-rsvg:

depends r-stringi:



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-chemminer

and update with::

   mamba update bioconductor-chemminer

To create a new environment, run:

mamba create --name myenvname bioconductor-chemminer

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

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