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
关键词
D O I
暂无
中图分类号
学科分类号
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.
引用
收藏
页码:368 / 372
页数:4
相关论文
共 50 条
  • [1] Neural network computation with DNA strand displacement cascades
    Qian, Lulu
    Winfree, Erik
    Bruck, Jehoshua
    [J]. NATURE, 2011, 475 (7356) : 368 - 372
  • [2] Scaling Up Digital Circuit Computation with DNA Strand Displacement Cascades
    Qian, Lulu
    Winfree, Erik
    [J]. SCIENCE, 2011, 332 (6034) : 1196 - 1201
  • [3] Robustness of Localized DNA Strand Displacement Cascades
    Teichmann, Mario
    Kopperger, Enzo
    Simmel, Friedrich C.
    [J]. ACS NANO, 2014, 8 (08) : 8487 - 8496
  • [4] Analog Computation by DNA Strand Displacement Circuits
    Song, Tianqi
    Garg, Sudhanshu
    Mokhtar, Reem
    Bui, Hieu
    Reif, John
    [J]. ACS SYNTHETIC BIOLOGY, 2016, 5 (08): : 898 - 912
  • [5] Implementing Feedforward Neural Network Using DNA Strand Displacement Reactions
    Zhu, Siyan
    Zhang, Qiang
    [J]. NANO, 2021, 16 (01)
  • [6] Catalytic DNA Strand Displacement Cascades Applied to Logic Programming
    Ordonez-Guillen, Nelson E.
    Martinez-Perez, Israel M.
    [J]. IEEE ACCESS, 2019, 7 : 100428 - 100441
  • [7] Simple Logic Computation Based on the DNA Strand Displacement
    Wang, Yanfeng
    Tian, Guihua
    Hou, Hewei
    Ye, Mengmeng
    Cui, Guangzhao
    [J]. JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE, 2014, 11 (09) : 1975 - 1982
  • [8] The Winner-Take-All Neural Network Based on DNA Strand Displacement
    Wang Bin
    Li Ya
    Zhao Hongwei
    [J]. JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY, 2021, 43 (08) : 2430 - 2438
  • [9] Exponential Function Computation Based on DNA Strand Displacement Circuits
    Wang, Yanfeng
    Mao, Tongtong
    Sun, Junwei
    Liu, Peng
    [J]. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, 2022, 16 (03) : 479 - 488
  • [10] Four-Analog Computation Based on DNA Strand Displacement
    Zou, Chengye
    Wei, Xiaopeng
    Zhang, Qiang
    Liu, Chanjuan
    Zhou, Changjun
    Liu, Yuan
    [J]. ACS OMEGA, 2017, 2 (08): : 4143 - 4160