recipe bioconductor-fmcsr

Mismatch Tolerant Maximum Common Substructure Searching






The fmcsR package introduces an efficient maximum common substructure (MCS) algorithms combined with a novel matching strategy that allows for atom and/or bond mismatches in the substructures shared among two small molecules. The resulting flexible MCSs (FMCSs) are often larger than strict MCSs, resulting in the identification of more common features in their source structures, as well as a higher sensitivity in finding compounds with weak structural similarities. The fmcsR package provides several utilities to use the FMCS algorithm for pairwise compound comparisons, structure similarity searching and clustering.

package bioconductor-fmcsr

(downloads) docker_bioconductor-fmcsr



depends bioconductor-biocgenerics:


depends bioconductor-biocgenerics:


depends bioconductor-chemminer:


depends bioconductor-chemminer:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-base:


depends r-runit:



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-fmcsr

and update with::

   mamba update bioconductor-fmcsr

To create a new environment, run:

mamba create --name myenvname bioconductor-fmcsr

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

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