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PyToDa

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Overview

pytoda - PaccMann PyTorch Dataset Classes

A python package that eases handling biochemical data for deep learning applications with pytorch.

Installation

pytoda ships via PyPI:

pip install pytoda

Documentation

Please find the full documentation here.

Development

For development setup, we recommend to work in a dedicated conda environment:

conda env create -f conda.yml

Activate the environment:

conda activate pytoda

Install in editable mode:

pip install -r dev_requirements.txt
pip install --user --no-use-pep517 -e .

Examples

For some examples on how to use pytoda see here

References

If you use pytoda in your projects, please cite the following:

@article{born2021data,
  title={Data-driven molecular design for discovery and synthesis of novel ligands: a case study on SARS-CoV-2},
  author={Born, Jannis and Manica, Matteo and Cadow, Joris and Markert, Greta and Mill, Nil Adell and Filipavicius, Modestas and Janakarajan, Nikita and Cardinale, Antonio and Laino, Teodoro and Martinez, Maria Rodriguez},
  journal={Machine Learning: Science and Technology},
  volume={2},
  number={2},
  pages={025024},
  year={2021},
  publisher={IOP Publishing}
}

Metadata

Release files for pytoda 1.1.7

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pytoda 1.1.7
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pytoda-1.1.7.tar.gz 200.2 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for pytoda 1.1.7
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pytoda-1.1.7-py3-none-any.whl Python 3 none any Details

Total release size: 437.3 kB

Release files / pytoda-1.1.7.tar.gz

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