文献
J-GLOBAL ID:202002280437580393
整理番号:20A1175368
機械学習誘導チャンネルロドプシン工学は最小侵襲光遺伝学を可能にする【JST・京大機械翻訳】
Machine learning-guided channelrhodopsin engineering enables minimally invasive optogenetics
著者 (7件):
Bedbrook Claire N.
(Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA)
,
Yang Kevin K.
(Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA)
,
Robinson J. Elliott
(Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA)
,
Mackey Elisha D.
(Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA)
,
Gradinaru Viviana
(Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA)
,
Arnold Frances H.
(Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA)
,
Arnold Frances H.
(Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA)
資料名:
Nature Methods
(Nature Methods)
巻:
16
号:
11
ページ:
1176-1184
発行年:
2019年
JST資料番号:
W1413A
ISSN:
1548-7091
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
ドイツ (DEU)
言語:
英語 (EN)