MultiMolecule¶
Tip
Accelerate Molecular Biology Research with Machine Learning
Introduction¶
Welcome to MultiMolecule (浦原), a foundational library designed to accelerate scientific research in molecular biology through machine learning. MultiMolecule provides a comprehensive yet flexible set of tools for researchers aiming to leverage AI with ease, focusing on biomolecular data (RNA, DNA, and protein).
Overview¶
MultiMolecule is built with flexibility and ease of use in mind. Its modular design allows you to utilize only the components you need, integrating seamlessly into your existing workflows without adding unnecessary complexity.
data
: SmartDataset
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.datasets
: A collection of widely-used biomolecular datasets.module
: Modular neural network building blocks, including embeddings, heads, and criterions for constructing custom models.models
: Implementation of state-of-the-art pre-trained models in molecular biology.tokenisers
: Tokenizers to convert DNA, RNA, protein and other sequences to one-hot encodings.
Installation¶
Install the most recent stable version on PyPI:
Bash | |
---|---|
Install the latest version from the source:
Bash | |
---|---|
Citation¶
If you use MultiMolecule in your research, please cite us as follows:
BibTeX | |
---|---|
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