2021
DOI: 10.1039/d0ra10515e
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Development of a neuron model based on DNAzyme regulation

Abstract: The neuron model regulated by DNAzymes is simple to construct and possesses strong scalability, having great potential for use in the construction of large neural networks.

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Cited by 4 publications
(3 citation statements)
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“…Similarly, DNAzyme and ASO associations that we have reported before have analyte recognizing modules that activate the associations′ RNA cleaving functions only after selective interaction with the analyte sequence [14,20,21,30] . Such dynamic DNA associations, that owe their responsiveness to DNA's inherent traits such as complementarity, can become intrinsic building blocks to DNA nanotechnology and molecular computational circuits [31–33] . Binary DNAzymes’ separated analyte recognition and target cleavage modules can be tailored to perfect their functionality independently from each other.…”
Section: Discussionmentioning
confidence: 91%
See 1 more Smart Citation
“…Similarly, DNAzyme and ASO associations that we have reported before have analyte recognizing modules that activate the associations′ RNA cleaving functions only after selective interaction with the analyte sequence [14,20,21,30] . Such dynamic DNA associations, that owe their responsiveness to DNA's inherent traits such as complementarity, can become intrinsic building blocks to DNA nanotechnology and molecular computational circuits [31–33] . Binary DNAzymes’ separated analyte recognition and target cleavage modules can be tailored to perfect their functionality independently from each other.…”
Section: Discussionmentioning
confidence: 91%
“…[14,20,21,30] Such dynamic DNA associations, that owe their responsiveness to DNA's inherent traits such as complementarity, can become intrinsic building blocks to DNA nanotechnology and molecular computational circuits. [31][32][33] Binary DNAzymes' separated analyte recognition and target cleavage modules can be tailored to perfect their functionality independently from each other. This feature makes them advantageous for molecular computation as they can be potentially designed to analyze complex molecular environments and perform complex logical operations.…”
Section: Discussionmentioning
confidence: 99%
“…Dediu et al [ 15 ] simulated the Boolean circuit using contextual hypergraph grammars techniques and further constructed the self-assembly of DNA tiles. In addition, half adder and half subtractor [ 16 , 17 , 18 ], full adder and full subtractor [ 19 , 20 , 21 ], encoder decoder [ 22 , 23 ], square root calculation [ 24 ], and neuron calculation model [ 25 ] have emerged. Qian and Winfree et al [ 26 ] proposed a “seesaw door” DNA motif based on DNA strand displacement technology, and on this basis, they further constructed a four-neuron Hopfield neural network computing model that can realize “heart guessing” [ 27 ] and winner-take-all neural network model [ 28 ]; this was breakthrough research in the field of molecular intelligent computing.…”
Section: Introductionmentioning
confidence: 99%