Metadata-Version: 1.1
Name: PyRhO
Version: 0.9.4
Summary: Fit and characterise rhodopsin photocurrents
Home-page: https://github.com/ProjectPyRhO/PyRhO/
Author: Benjamin D. Evans
Author-email: ben.d.evans@gmail.com
License: BSD
Description: 
        PyRhO - A Virtual Optogenetics Laboratory
        =========================================
        
        A Python module to fit and characterise rhodopsin photocurrents
        
        Optogenetics has become a key tool for understanding the function of neural circuits and controlling their behaviour. An array of directly light driven opsins have been genetically isolated from several families of organisms, with a wide range of temporal and spectral properties. In order to characterize, understand and apply these rhodopsins, we present an integrated suite of open-source, multi-scale computational tools called PyRhO. 
        
        The purpose of developing PyRhO is threefold: 
        
        (i) to characterize new (and existing) rhodopsins by automatically fitting a minimal set of experimental data to three, four or six-state kinetic models, 
        (ii) to simulate these models at the channel, neuron & network levels and 
        (iii) provide functional insights through model selection and virtual experiments *in silico*. 
        
        The module is written in Python with an additional IPython/Jupyter notebook based GUI, allowing models to be fit, simulations to be run and results to be shared through simply interacting with a webpage. The seamless integration of model fitting algorithms with simulation environments for these virtual opsins will enable neuroscientists to gain a comprehensive understanding of their behaviour and rapidly identify the most suitable variant for application in a particular biological system. This process may thereby guide not only experimental design and opsin choice but also alterations of the rhodopsin genetic code in a neuro-engineering feed-back loop. In this way, we expect PyRhO will help to significantly improve optogenetics as a tool for transforming biological sciences. 
        
        If you use PyRhO please cite our paper: 
        
        Evans, B. D., Jarvis, S., Schultz, S. R. & Nikolic K. (2016) "PyRhO: A Multiscale Optogenetics Simulation Platform", *Front. Neuroinform., 10* (8). `doi:10.3389/fninf.2016.00008 <https://dx.doi.org/10.3389/fninf.2016.00008>`_
        
        The PyRhO project website with additional documentation may be found here: `www.imperial.ac.uk/bio-modelling/pyrho <http://www.imperial.ac.uk/a-z-research/bio-modelling/pyrho>`_
        
        
        
Keywords: optogenetics rhodopsin opsin brain neuroscience neuron brian jupyter
Platform: Linux
Platform: Mac OS X
Platform: Windows
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Artificial Life
Classifier: Topic :: Scientific/Engineering :: Human Machine Interfaces
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.1
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Framework :: IPython
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
