Metadata-Version: 2.1
Name: protlearn
Version: 0.0.2
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/v0.0.2.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://anaconda.org/conda-forge/protlearn"><img alt="Conda version" src="https://img.shields.io/conda/vn/conda-forge/protlearn.svg"></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. 
        
        ## Overview
        
        <p align="center">
          <img src="/imgs/protlearn_summary.png" height="430" width="624">
        </p>
        
        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 -c conda-forge 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
