Neural network computation with DNA strand displacement cascades

被引:0
作者
Lulu Qian
Erik Winfree
Jehoshua Bruck
机构
[1] Bioengineering,
[2] California Institute of Technology,undefined
[3] Computer Science,undefined
[4] California Institute of Technology,undefined
[5] Computation and Neural Systems,undefined
[6] California Institute of Technology,undefined
[7] Electrical Engineering,undefined
[8] California Institute of Technology,undefined
来源
Nature | 2011年 / 475卷
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摘要
Before neuron-based brains evolved, complex biomolecular circuits must have endowed individual cells with the intelligent behaviour that ensures survival. But the study of how molecules can 'think' has not yet produced useful molecule-based computational systems that mimic even a single neuron. In a study that straddles the fields of DNA nanotechnology, DNA computing and synthetic biology, Qian et al. use DNA as an engineering material to construct computing circuits that exhibit autonomous brain-like behaviour. The team uses a simple DNA gate architecture to create reaction cascades functioning as a 'Hopfield associative memory', which can be trained to 'remember' DNA patterns and recall the most similar one when presented with an incomplete pattern. The challenge now is to use the strategy to design autonomous chemical systems that can recognize patterns or molecular events, make decisions and respond to the environment.
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页码:368 / 372
页数:4
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