Metadata-Version: 2.1
Name: protlearn
Version: 0.0.1
Summary: A Python package for extracting protein sequence features
Home-page: https://github.com/tadorfer/protlearn
Author: Thomas Dorfer
Author-email: thomas.a.dorfer@gmail.com
License: MIT
Download-URL: https://github.com/tadorfer/protlearn/archive/v0.0.1.tar.gz
Description: <p align="center">
          <img src="https://raw.githubusercontent.com/tadorfer/protlearn/master/imgs/protlearn_logo.png" height="85" width="230">
        </p>
        
        <p align="center">
          A Python package for extracting protein sequence features
          <br>
          <a href="https://protlearn.readthedocs.io/en/latest/">Documentation</a>
          ·
          <a href="https://github.com/tadorfer/protlearn/issues/new?assignees=&labels=&template=feature_request.md&title=%5BNEW+FEATURE%5D">Request a feature</a>
          · 
          <a href="https://github.com/tadorfer/protlearn/issues/new?assignees=&labels=&template=bug_report.md&title=%5BBUG%5D">Report a bug</a>
          <br><br>
          <a href="https://travis-ci.org/tadorfer/protlearn"><img alt="Travis CI" src="https://img.shields.io/travis/tadorfer/protlearn"></a>
          <a href="https://codecov.io/gh/tadorfer/protlearn"><img alt="Codecov" src="https://codecov.io/gh/tadorfer/protlearn/branch/master/graph/badge.svg"></a>
          <a href="https://protlearn.readthedocs.io/en/latest/?badge=latest"><img alt="Docs" src="https://readthedocs.org/projects/protlearn/badge/?version=latest"></a> 
          <a href="https://pypi.org/project/protlearn/"><img alt="PyPI" src="https://img.shields.io/pypi/v/protlearn"></a>
          <a href="https://img.shields.io/pypi/pyversions/protlearn"><img alt="Python versions" src="https://img.shields.io/pypi/pyversions/protlearn"></a>  
          <a href="https://lbesson.mit-license.org/"><img alt="License" src="https://img.shields.io/badge/License-MIT-blue.svg"></a>   
        </p>
        <hr><br>
        
        *protlearn* is a Python package for the feature extraction of amino acid sequences.
        It is comprised of three stages - preprocessing, feature computation, and 
        subsequent dimensionality reduction. Currently, the package is being maintained 
        for Python versions 3.6, 3.7, and 3.8. 
        
        For more information on how to use it, please refer to the [documentation](https://protlearn.readthedocs.io/en/latest/).
        
        ## Installation
        
        ### Dependencies
        
        - NumPy 
        - Pandas 
        - scikit-learn
        - xgboost
        - mlxtend
        - biopython
        
        ### User Installation
        
        #### PyPI
        
        You can install _protlearn_ with `pip`:
        
        ```
        $ pip install protlearn
        ```
        
        #### Conda
        
        You can install _protlearn_ with `conda`:
        
        ```
        $ conda install protlearn
        ```
        
        ## Authors
        
        This package is maintained by [Thomas Dorfer](https://github.com/tadorfer).
        
        ## License
        
        This package is licensed under the [MIT License](https://github.com/tadorfer/ProtLearn/blob/master/LICENSE).
Keywords: amino acids,proteins,peptides,preprocessing,feature engineering,dimensionality reduction,machine learning
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
