In vitro convolutional neural networks

被引：4

作者：

Poole, William ^{[1
]}

机构：

[1] CALTECH, Computat & Neural Syst, Pasadena, CA 91125 USA

来源：

NATURE MACHINE INTELLIGENCE | 2022年 / 4卷 / 07期

关键词：

D O I：

10.1038/s42256-022-00508-1

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Neural networks can be implemented by using purified DNA molecules that interact in a test tube. Convolutional neural networks to classify high-dimensional data have now been realized in vitro, in one of the most complex demonstrations of molecular programming so far.

引用

页码：614 / 615

页数：2

共 8 条

[1] Scaling up molecular pattern recognition with DNA-based winner-take-all neural networks [J].

Cherry, Kevin M. ;

Qian, Lulu .

NATURE, 2018, 559 (7714) :370-+

[2]

Fukushima K, 1982, COMPETITION COOPERAT, P267

[3] Recent advances in convolutional neural networks [J].

Gu, Jiuxiang ;

Wang, Zhenhua ;

Kuen, Jason ;

Ma, Lianyang ;

Shahroudy, Amir ;

Shuai, Bing ;

Liu, Ting ;

Wang, Xingxing ;

Wang, Gang ;

Cai, Jianfei ;

Chen, Tsuhan .

PATTERN RECOGNITION, 2018, 77 :354-377

[4] Genetic circuit design automation with Cello 2.0 [J].

Jones, Timothy S. ;

Oliveira, Samuel M. D. ;

Myers, Chris J. ;

Voigt, Christopher A. ;

Densmore, Douglas .

NATURE PROTOCOLS, 2022, 17 (04) :1097-1113

[5] Neural network computation with DNA strand displacement cascades [J].

Qian, Lulu ;

Winfree, Erik ;

Bruck, Jehoshua .

NATURE, 2011, 475 (7356) :368-372

[6] DNA nanotechnology [J].

Seeman, Nadrian C. ;

Sleiman, Hanadi F. .

NATURE REVIEWS MATERIALS, 2018, 3 (01)

[7]

Xiong X., NAT MACH INTELL, DOI [10.1038/s42256-022-00502-7(2022), DOI 10.1038/S42256-022-00502-7(2022)]

[8]

Zhang DY, 2011, NAT CHEM, V3, P103, DOI [10.1038/nchem.957, 10.1038/NCHEM.957]

← 1 →