DNA computing: Difference between revisions

Revision as of 14:32, 5 April 2024

Revision as of 14:33, 5 April 2024

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=== Improved speed with Localized (cache-like) Computing ===

One of the challenges of DNA computing is its speed. While DNA as a substrate is biologically compatible i.e. it can be used at places where silicon technology cannot, its computation speed is still very slow. For example, the square-root circuit used as a benchmark in field took over 100 hours to complete.<ref name=":5">{{Cite journal|last1=Qian|first1=L.|last2=Winfree|first2=E.|s2cid=10053541|date=2011-06-02|title=Scaling Up Digital Circuit Computation with DNA Strand Displacement Cascades|journal=Science|volume=332|issue=6034|pages=1196–1201|doi=10.1126/science.1200520|pmid=21636773|issn=0036-8075|bibcode=2011Sci...332.1196Q}}</ref> While newer ways with external enzyme sources are reporting faster and more compact circuits,<ref name=":6">{{Cite journal|last1=Song|first1=Tianqi|last2=Eshra|first2=Abeer|last3=Shah|first3=Shalin|last4=Bui|first4=Hieu|last5=Fu|first5=Daniel|last6=Yang|first6=Ming|last7=Mokhtar|first7=Reem|last8=Reif|first8=John|date=2019-09-23|title=Fast and compact DNA logic circuits based on single-stranded gates using strand-displacing polymerase|journal=Nature Nanotechnology|volume=14|issue=11|pages=1075–1081|doi=10.1038/s41565-019-0544-5|pmid=31548688|issn=1748-3387|bibcode=2019NatNa..14.1075S|s2cid=202729100}}</ref> Chatterjee et al. demonstrated an interesting idea in the field to speed up computation through localized DNA circuits.<ref>{{Cite journal|last1=Chatterjee|first1=Gourab|last2=Dalchau|first2=Neil|last3=Muscat|first3=Richard A.|last4=Phillips|first4=Andrew|last5=Seelig|first5=Georg|date=2017-07-24|title=A spatially localized architecture for fast and modular DNA computing|journal=Nature Nanotechnology|volume=12|issue=9|pages=920–927|doi=10.1038/nnano.2017.127|pmid=28737747|issn=1748-3387|bibcode=2017NatNa..12..920C}}</ref> This concept is being further explored by other groups.<ref name=":9">{{Cite journal|last1=Bui|first1=Hieu|last2=Shah|first2=Shalin|last3=Mokhtar|first3=Reem|last4=Song|first4=Tianqi|last5=Garg|first5=Sudhanshu|last6=Reif|first6=John|date=2018-01-25|title=Localized DNA Hybridization Chain Reactions on DNA Origami|journal=ACS Nano|volume=12|issue=2|pages=1146–1155|doi=10.1021/acsnano.7b06699|pmid=29357217|issn=1936-0851}}</ref> This idea, while originally proposed in the field of computer architecture, has been adopted in this field as well. In computer architecture, it is very well-known that if the instructions are executed in sequence, having them loaded in the cache will inevitably lead to fast performance, also called as the principle of localization. This is because with instructions in fast cache memory, there is no need swap them in and out of main memory, which can be slow. Similarly, in [https://www.nature.com/articles/nnano.2017.127 localized DNA computing], the DNA strands responsible for computation are fixed on a breadboard-like substrate ensuring physical proximity of the computing gates. Such localized DNA computing techniques have shown to potentially reduce the computation time by [https://www.nature.com/articles/nnano.2017.127 orders of magnitude].

=== Renewable (or reversible) DNA computing ===