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10.3389/fninf.2016.00008 http://scihub22266oqcxt.onion/10.3389/fninf.2016.00008 C4834562!4834562 !27148037     free     free     free Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\27148037 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Front+Neuroinform 2016 ; 10 (ä): 8 Nephropedia Template TP {{tp|p=27148037 |t=2016. PyRhO: A Multiscale Optogenetics Simulation Platform |pdf=|usr=}}{{27148037 }} gab.com Text PyRhO: A Multiscale Optogenetics Simulation Platform JO: Front Neuroinform http://www.kidney.de/pget.php?&tw=1&pmid=27148037 #FOAvip Optogenetics has become a key tool for understanding the function of neural circuits and controlling their behavior. 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 opsins, we present an integrated suite of open-source, multi-scale computational tools called PyRhO. The purpose of developing PyRhO is three-fold: (i) to characterize new (and existing) opsins 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 and 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 (including NEURON and Brian2) for these virtual opsins will enable neuroscientists to gain a comprehensive understanding of their behavior 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 opsin genetic code in a neuro-engineering feed-back loop. In this way, we expect PyRhO will help to significantly advance optogenetics as a tool for transforming biological sciences. Twit Text FOAVip PyRhO: A Multiscale Optogenetics Simulation Platform ????Front Neuroinform http://www.kidney.de/pget.php?&tw=1&pmid=27148037 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27148037 #FOAvip English Wikipedia <ref>{{Cite pmid|27148037 }}</ref> PyRhO: A Multiscale Optogenetics Simulation Platform #MMPMID27148037 Evans BD ; Jarvis S ; Schultz SR ; Nikolic K Front Neuroinform 2016[]; 10 (ä): 8 PMID27148037 show ga Optogenetics has become a key tool for understanding the function of neural circuits and controlling their behavior. 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 opsins, we present an integrated suite of open-source, multi-scale computational tools called PyRhO. The purpose of developing PyRhO is three-fold: (i) to characterize new (and existing) opsins 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 and 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 (including NEURON and Brian2) for these virtual opsins will enable neuroscientists to gain a comprehensive understanding of their behavior 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 opsin genetic code in a neuro-engineering feed-back loop. In this way, we expect PyRhO will help to significantly advance optogenetics as a tool for transforming biological sciences. äPyRhO: A Multiscale Optogenetics Simulation Platform (epmc).pdf DeepDyve Pubget Overpricing