Metadata-Version: 2.1
Name: proteinko
Version: 2.0.0
Summary: Signal representation of physicochemical properties of proteins
Home-page: https://github.com/stefs304/proteinko
Author: Stefan Stojanovic
Author-email: stefs304@gmail.com
License: UNKNOWN
Description: # Proteinko
        
        [README на српском](https://github.com/stefs304/proteinko/blob/master/README_srb.md)
        
        Proteinko is package that enables you to represent a protein sequence (that is
         its physicochemical properties) as spatial signals.
        
        Protein is a sequence of amino acid residues, each of which has characteristic physical and chemical properties.
        Local properties of a protein are reflection of local cumulative effect of amino acid residues that make up said protein.
        By modeling physico-chemical properties for each amino acid residue as a normal distribution spanning the neighbouring amino acid 
        residues, we obtain a continuous signal which represents a spatial distribution of specific physicochemical property of a protein.
        
        This way we can represent a protein sequence as a distribution of following properties:
        * hydropathy
        * donor atoms
        * acceptor atoms
        * isoelectric point
        * molecular volume
        
        Proteinko also allows for usage of custom amino acid residue scales.
        
        Manuscript ready for publishing.
        
        ### Example
        ![signals](https://raw.githubusercontent.com/stefs304/proteinko/master/example.png)
        
        ### Installation
        ```buildoutcfg
        pip install proteinko
        ```
        
        ### Usage
        
        ```
        from proteinko import ProteinSignal
        
        sequence = <your_protein_sequence>
        protein = ProteinSignal()
        signal = protein.get_signal(sequence, 'hydropathy')
        
        ## ...Now play with the signal however you like
        ```
        
        ### Contact and portfolio
        
        * My [Linkedin](https://rs.linkedin.com/in/stefan-stojanovic-304) profile.
        * [MHCLovac](https://github.com/stefs304/mhclovac) - in this repository protein signals are usded to predict MHC binding.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 2
Classifier: License :: OSI Approved :: MIT License
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Healthcare Industry
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Chemistry
Description-Content-Type: text/markdown
