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Quality](https://app.codacy.com/project/badge/Grade/ad5fd8904c2e426bb0a865a9160d6c69)](https://app.codacy.com/gh/DLS5-Omics/multimolecule/dashboard?utm_source=gh\u0026utm_medium=referral\u0026utm_content=\u0026utm_campaign=Badge_grade)\n[![Codacy - Coverage](https://app.codacy.com/project/badge/Coverage/ad5fd8904c2e426bb0a865a9160d6c69)](https://app.codacy.com/gh/DLS5-Omics/multimolecule/dashboard?utm_source=gh\u0026utm_medium=referral\u0026utm_content=\u0026utm_campaign=Badge_coverage)\n[![CodeCov - Coverage](https://codecov.io/gh/DLS5-Omics/multimolecule/graph/badge.svg?token=G9WGWCOFQE)](https://codecov.io/gh/DLS5-Omics/multimolecule)\n\n[![PyPI - Version](https://img.shields.io/pypi/v/multimolecule)](https://pypi.org/project/multimolecule)\n[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/multimolecule)](https://pypi.org/project/multimolecule)\n[![Downloads Statistics](https://static.pepy.tech/badge/multimolecule/month)](https://multimolecule.danling.org)\n\n[![License: AGPL v3](https://img.shields.io/badge/License-AGPL%20v3-blue.svg)](https://www.gnu.org/licenses/agpl-3.0)\n\n## Introduction\n\nWelcome to MultiMolecule (浦原), a foundational library designed to accelerate scientific research in molecular biology through machine learning.\nMultiMolecule provides a comprehensive yet flexible set of tools for researchers aiming to leverage AI with ease, focusing on biomolecular data (RNA, DNA, and protein).\n\n## Overview\n\nMultiMolecule is built with flexibility and ease of use in mind.\nIts modular design allows you to utilize only the components you need, integrating seamlessly into your existing workflows without adding unnecessary complexity.\n\n- [`data`](data): Smart [`Dataset`][multimolecule.data.Dataset] that automatically infer tasks—including their level (sequence, token, contact) and type (classification, regression). Provides multi-task datasets and samplers to facilitate multitask learning without additional configuration.\n- [`datasets`](datasets): A collection of widely-used biomolecular datasets.\n- [`modules`](modules): Modular neural network building blocks, including [embeddings](modules/embeddings), [heads](modules/heads), and criterions for constructing custom models.\n- [`models`](models): Implementation of state-of-the-art pre-trained models in molecular biology.\n- [`tokenisers`](tokenisers): Tokenizers to convert DNA, RNA, protein and other sequences to one-hot encodings.\n\u003c!-- - [`runner`](runner): A powerful and extensible runner allows users to fine-tune models, evaluate and predict with ease. --\u003e\n\n## Installation\n\nInstall the most recent stable version on PyPI:\n\n```shell\npip install multimolecule\n```\n\nInstall the latest version from the source:\n\n```shell\npip install git+https://github.com/DLS5-Omics/MultiMolecule\n```\n\n## Citation\n\n\u003e [!NOTE]\n\u003e The artifacts distributed in this repository are part of the MultiMolecule project.\n\u003e If you use MultiMolecule in your research, you must cite the MultiMolecule project as follows:\n\n```bibtex\n@software{chen_2024_12638419,\n  author    = {Chen, Zhiyuan and Zhu, Sophia Y.},\n  title     = {MultiMolecule},\n  doi       = {10.5281/zenodo.12638419},\n  publisher = {Zenodo},\n  url       = {https://doi.org/10.5281/zenodo.12638419},\n  year      = 2024,\n  month     = may,\n  day       = 4\n}\n```\n\n## License\n\nWe believe openness is the Foundation of Research.\n\nMultiMolecule is licensed under the [GNU Affero General Public License](license.md).\n\nFor additional terms and clarifications, please refer to our [License FAQ](license-faq.md).\n\nPlease join us in building an open research community.\n\n`SPDX-License-Identifier: AGPL-3.0-or-later`\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdls5-omics%2Fmultimolecule","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdls5-omics%2Fmultimolecule","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdls5-omics%2Fmultimolecule/lists"}