recipe bioconductor-ppinfer

Inferring functionally related proteins using protein interaction networks






Interactions between proteins occur in many, if not most, biological processes. Most proteins perform their functions in networks associated with other proteins and other biomolecules. This fact has motivated the development of a variety of experimental methods for the identification of protein interactions. This variety has in turn ushered in the development of numerous different computational approaches for modeling and predicting protein interactions. Sometimes an experiment is aimed at identifying proteins closely related to some interesting proteins. A network based statistical learning method is used to infer the putative functions of proteins from the known functions of its neighboring proteins on a PPI network. This package identifies such proteins often involved in the same or similar biological functions.

package bioconductor-ppinfer

(downloads) docker_bioconductor-ppinfer



depends bioconductor-biomart:


depends bioconductor-fgsea:


depends bioconductor-stringdb:


depends bioconductor-yeastexpdata:


depends r-base:


depends r-ggplot2:

depends r-httr:

depends r-igraph:

depends r-kernlab:



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-ppinfer

and update with::

   mamba update bioconductor-ppinfer

To create a new environment, run:

mamba create --name myenvname bioconductor-ppinfer

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

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