Metadata-Version: 2.1
Name: jax-unirep
Version: 1.0
Summary: A performant and user-friendly reimplementation of UniRep in JAX.
Home-page: https://github.com/ElArkk/jax-unirep
Author: Arkadij Kummer, Eric J. Ma, Ivan Jayapurna
Author-email: arkadij.kummer@gmail.com, ericmajinglong@gmail.com, ivanfj@berkeley.edu
License: UNKNOWN
Description: [![Build Status](https://travis-ci.com/ElArkk/jax-unirep.svg?branch=master)](https://travis-ci.com/ElArkk/jax-unirep)
        [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
        
        # jax-unirep
        
        A performant reimplementation of the UniRep protein featurization model in JAX.
        
        The UniRep model was developed in George Church's lab,
        see the original publication
        [here][arxiv] (bioRxiv) or [here][nature] (Nature Methods),
        as well as the [repository][repo] containing the original model.
        
        This repo is a self-contained version of the UniRep model
        (so far only the 1900 hidden-unit mLSTM),
        with additional utility APIs that support protein engineering workflows.
        
        ## Installation
        
        Ensure that your compute environment allows you to run JAX code.
        (A modern Linux or macOS with a GLIBC>=2.23 is probably necessary.)
        
        For now, `jax-unirep` is available by pip installing from source.
        
        Installation from GitHub:
        
        ```bash
        pip install git+https://github.com/ElArkk/jax-unirep.git
        ```
        
        ## More Details
        
        Documentation on how to use `jax-unirep` is available [here][docs].
        
        We highly encourage community contributions to this project! For more information, see the section in the docs on our [contributing][cont] guidelines.
        
        
        To read more about how we reimplemented the model in JAX,
        check out our preprint
        on [bioarxiv](https://www.biorxiv.org/content/10.1101/2020.05.11.088344v1).
        
        
        ## License
        
        All the model weights are licensed under the terms of
        Creative Commons Attribution-NonCommercial 4.0 International License.
        To view a copy of this license,
        visit [here](http://creativecommons.org/licenses/by-nc/4.0/)
        or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.
        
        Otherwise the code in this repository
        is licensed under the terms of [GPL v3][gpl3].
        
        [arxiv]: https://www.biorxiv.org/content/10.1101/589333v1
        [nature]: https://www.nature.com/articles/s41592-019-0598-1
        [repo]: https://github.com/churchlab/UniRep
        [ericmjl]: https://github.com/ericmjl
        [fundl]: https://github.com/ericmjl/fundl
        [gpl3]: https://www.gnu.org/licenses/gpl-3.0.html
        [evotunefunc]: https://github.com/ElArkk/jax-unirep/blob/master/jax_unirep/evotuning.py#L421
        [fitfunc]: https://github.com/ElArkk/jax-unirep/blob/master/jax_unirep/evotuning.py#L163
        [examples]: https://github.com/ElArkk/jax-unirep/blob/master/examples
        [stax]: https://jax.readthedocs.io/en/latest/jax.experimental.stax.html
        [staxex]: https://github.com/google/jax/tree/master/examples
        [docs]: https://elarkk.github.io/jax-unirep/
        [cont]: https://elarkk.github.io/jax-unirep/contributing/
        [it]: https://github.com/ElArkk/jax-unirep/issues
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Healthcare Industry
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Chemistry
Requires-Python: >=3.7
Description-Content-Type: text/markdown
