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MultiMolecule

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Accelerate Molecular Biology Research with Machine Learning

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License: AGPL v3

🧬 Introduction

MultiMolecule is a framework that bridges molecular biology and machine learning. It offers machine learning tools specifically designed for biomolecular data (RNA, DNA, and protein).

MultiMolecule serves as a foundation for advancing research at the intersection of molecular biology and machine learning.

πŸš€ Features

πŸ“‘ Resources

πŸ› οΈ Tools

  • pipelines: End-to-end workflows for applying models.
  • runner: Automatic Runner for training models.

βš™οΈ Infrastructure

  • data: Smart Dataset that automatically infer tasksβ€”including their level (sequence, token, contact) and type (classification, regression).
  • tokenisers: Tokenizers for biomolecular sequences.
  • module: Neural network building blocks.

πŸ”§ Installation

Bash
pip install multimolecule
Bash
pip install git+https://github.com/DLS5-Omics/multimolecule

πŸ“œ Citation

If you use MultiMolecule in your research, please cite us as follows:

BibTeX
@software{chen_2024_12638419,
  author    = {Chen, Zhiyuan and Zhu, Sophia Y.},
  title     = {MultiMolecule},
  doi       = {10.5281/zenodo.12638419},
  publisher = {Zenodo},
  url       = {https://doi.org/10.5281/zenodo.12638419},
  year      = 2024,
  month     = may,
  day       = 4
}

πŸ“„ License

We believe openness is the Foundation of Research.

MultiMolecule is licensed under the GNU Affero General Public License.

For additional terms and clarifications, please refer to our License FAQ.

Please join us in building an open research community.

SPDX-License-Identifier: AGPL-3.0-or-later