Metadata-Version: 2.1
Name: pyADAqsar
Version: 1.0.3
Summary: A cheminformatics package to perform Applicability Domain of molecular fingerprints based in similarity calculation.
Home-page: https://github.com/jeffrichardchemistry/pyADA
Author: Jefferson Richard
Author-email: jrichardquimica@gmail.com
License: GNU GPL
Description: [![DOI](https://zenodo.org/badge/340351316.svg)](https://zenodo.org/badge/latestdoi/340351316)
        
        
        # pyADA
        pyADA (Python Applicability Domain Analyzer) is a cheminformatics package to perform Applicability Domain of molecular fingerprints based in similarity calculation.
        In this case, the calculation of the Applicability Domain consists of a scan of similarities of the structures
        present in the test set in relation to the training set, the best similarity threshold is the one with the lowest
        error and also the lowest number of molecules with similarity below the threshold. 
        A notebook file with an example of using this package is present in the directory 'example/example_of_use.ipynb'
        ### Dependencies
        <ul>
        <li><b>numpy</b></li>
        <li><b>pandas</b></li>
        <li><b>tqdm</b></li>
        <li><b>scikit-learn</b></li>
        <li><b>Tested in python3.6 and python3.8</b></li>
        </ul>
        
        ## Install
        <b>Via pip</b>
        ```
        pip3 install pyADAqsar
        ```
        
        <b>Via github</b>
        ```
        git clone https://github.com/jeffrichardchemistry/pyADA
        cd pyADA
        python3 setup.py install
        ```
        
        ## How to use
        This package has three classes: Smetrics (perform some statistical parameters like Q2ext R2ext etc), Similarity (realize similarity calculations based in differents metrics ) and ApplicabilityDomain (run a scan of AD with differents thresholds). The line code bellow import all classes.
        ```
        from pyADA import Smetrics, Similarity, ApplicabilityDomain
        ```
        A file containing a jupyter-notebook with a few examples of use is in 'example' folder.
        For more information about documentation run the help function of classes.
        ```
        help(Smetrics)
        help(Similarity)
        help(ApplicabilityDomain)
        ```
        
Keywords: Cheminformatics,Chemistry,Applicability Domain,QSAR,SAR,Molecular Fingerprint
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Natural Language :: English
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Environment :: MacOS X
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
