recipe sbpipe

SBpipe is a collection of pipelines for systems modelling of biological networks. It allows mathematical modellers to automatically repeat the tasks of model simulation and parameter estimation, and extract robustness information from these repeat sequences in a solid and consistent manner, facilitating model development and analysis. SBpipe can run models implemented in COPASI, Python or coded in any other programming language using Python as a wrapper module. Pipelines can run on multicore computers, Sun Grid Engine (SGE), Load Sharing Facility (LSF) clusters, or via Snakemake.

Homepage:

http://sbpipe.readthedocs.io

License:

MIT

Recipe:

/sbpipe/meta.yaml

Links:

doi: 10.1186/s12918-017-0423-3

package sbpipe

(downloads) docker_sbpipe

versions:

4.21.0-1,  4.21.0-0,  4.20.0-0,  4.18.0-0

depends colorlog:

depends python:

depends pyyaml:

depends r-sbpiper:

1.8.*

requirements:

Installation

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 sbpipe

and update with::

   mamba update sbpipe

To create a new environment, run:

mamba create --name myenvname sbpipe

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 quay.io/biocontainers/sbpipe:<tag>

(see `sbpipe/tags`_ for valid values for ``<tag>``)

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Link to this page

Render an install-with-bioconda badge with the following MarkDown:

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