- recipe promod3
ProMod3 is a tool for protein structure prediction and refinement
- Homepage:
- Developer docs:
- License:
Apache / Apache-2.0
- Recipe:
- Links:
biotools: promod3, doi: 10.1371/journal.pcbi.1008667
ProMod3 is a modelling engine based on the OpenStructure computational structural biology framework (www.openstructure.org) that can perform all steps required to generate a protein model by homology. Its modular design aims at implementing flexible modelling pipelines and fast prototyping of novel algorithms.
- package promod3¶
-
- Versions:
3.6.0-0,3.5.0-0- Depends:
on libboost
>=1.86.0,<1.87.0a0on libboost-python
>=1.86.0,<1.87.0a0on libgcc
>=13on libstdcxx
>=13on openmm
>=8.3.1,<9.0a0on openstructure
>=2.11.0,<2.12.0a0on python
>=3.10,<3.11.0a0 *_cpythonon python_abi
3.10.* *_cp310
- Additional platforms:
linux-aarch64,osx-arm64
Installation¶
You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).
Pixi¶
With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:
pixi global install promod3
to add into an existing workspace instead, run:
pixi add promod3
In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:
pixi workspace channel add conda-forge
pixi workspace channel add bioconda
Conda¶
With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:
conda install promod3
Alternatively, to install into a new environment, run:
conda create -n envname promod3
with envname being the name of the desired environment.
Container¶
Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:
docker pull quay.io/biocontainers/promod3:<tag>
(see promod3/tags for valid values for <tag>).
Integrated deployment¶
Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.
Download stats¶
Link to this page¶
Render an badge with the following MarkDown:
[](http://bioconda.github.io/recipes/promod3/README.html)