Package Recipe 'b2btools'

recipe b2btools

The bio2Byte software suite to predict protein biophysical properties.

Homepage:: https://bio2byte.be/b2btools
Developer docs:: https://bitbucket.org/bio2byte/b2btools_releases
License:: GPL3 / GPL-3.0-or-later
Recipe:: /b2btools/meta.yaml
Links:: doi: 10.48550/arXiv.2405.02136, biotools: b2btools

This package provides you with structural predictions for protein sequences made by the Bio2Byte group which researches the relation between protein sequence and biophysical behavior.

List of available predictors: 1. Dynamine: Fast predictor of protein backbone dynamics using only sequence information as input. The version here also predicts side-chain dynamics and secondary structure predictors using the same principle. 2. Disomine: Predicts protein disorder with recurrent neural networks not directly from the amino acid sequence, but instead from more generic predictions of key biophysical properties, here protein dynamics, secondary structure, and early folding. 3. EfoldMine: Predicts from the primary amino acid sequence of a protein, which amino acids are likely involved in early folding events. 4. AgMata: Single-sequence-based predictor of protein regions that are likely to cause beta-aggregation. 5. PSPer: PSP (Phase Separating Protein) predicts whether a protein is likely to phase-separate with a particular mechanism involving RNA interacts (FUS-like proteins). 6. ShiftCrypt: Auto-encoding NMR chemical shifts from their native vector space to a residue-level biophysical index.

package b2btools¶

Versions:

3.0.7-3, 3.0.7-2, 3.0.7-1, 3.0.7-0, 3.0.6-0, 3.0.5-0, 3.0.4-0

Depends:

on biopython >=1.83,<2
on hmmer
on joblib >=0.9.0b4
on libgcc >=14
on libstdcxx >=14
on matplotlib-base >=3.5.3,<3.6
on networkx >=2.4
on numpy >=1.21.6,<1.27
on numpy >=1.26.4,<2.0a0
on pandas >=1.5.3
on python >=3.10,<3.11.0a0
on python_abi 3.10.* *_cp310
on pytorch >=1.11.0,<=1.13.1
on pyyaml
on requests >=2.31.0,<2.32
on scikit-learn 1.0.2
on scipy 1.12.0
on t-coffee
on urllib3 >=1.26.6,<1.27

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 b2btools

to add into an existing workspace instead, run:

pixi add b2btools

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 b2btools

Alternatively, to install into a new environment, run:

conda create -n envname b2btools

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/b2btools:<tag>

(see b2btools/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:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/b2btools/README.html)