Bedbrook, Claire N., Yang, Kevin K., Robinson, J. Elliott, Mackey, Elisha D., Gradinaru, Viviana, and Arnold, Frances H. Machine learning-guided channelrhodopsin engineering enables minimally invasive optogenetics. Retrieved from https://par.nsf.gov/biblio/10189008. Nature Methods 16.11 Web. doi:10.1038/s41592-019-0583-8.

Bedbrook, Claire N., Yang, Kevin K., Robinson, J. Elliott, Mackey, Elisha D., Gradinaru, Viviana, & Arnold, Frances H. Machine learning-guided channelrhodopsin engineering enables minimally invasive optogenetics. Nature Methods, 16 (11). Retrieved from https://par.nsf.gov/biblio/10189008. https://doi.org/10.1038/s41592-019-0583-8

Bedbrook, Claire N., Yang, Kevin K., Robinson, J. Elliott, Mackey, Elisha D., Gradinaru, Viviana, and Arnold, Frances H. "Machine learning-guided channelrhodopsin engineering enables minimally invasive optogenetics". Nature Methods 16 (11). Country unknown/Code not available. https://doi.org/10.1038/s41592-019-0583-8. https://par.nsf.gov/biblio/10189008.

@article{osti_10189008,
place = {Country unknown/Code not available}, title = {Machine learning-guided channelrhodopsin engineering enables minimally invasive optogenetics}, url = {https://par.nsf.gov/biblio/10189008}, DOI = {10.1038/s41592-019-0583-8}, abstractNote = {}, journal = {Nature Methods}, volume = {16}, number = {11}, author = {Bedbrook, Claire N. and Yang, Kevin K. and Robinson, J. Elliott and Mackey, Elisha D. and Gradinaru, Viviana and Arnold, Frances H.}, }