Programmable and autonomous computing machine made of biomolecules View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2001-11

AUTHORS

Yaakov Benenson, Tamar Paz-Elizur, Rivka Adar, Ehud Keinan, Zvi Livneh, Ehud Shapiro

ABSTRACT

Devices that convert information from one form into another according to a definite procedure are known as automata. One such hypothetical device is the universal Turing machine, which stimulated work leading to the development of modern computers. The Turing machine and its special cases, including finite automata, operate by scanning a data tape, whose striking analogy to information-encoding biopolymers inspired several designs for molecular DNA computers. Laboratory-scale computing using DNA and human-assisted protocols has been demonstrated, but the realization of computing devices operating autonomously on the molecular scale remains rare. Here we describe a programmable finite automaton comprising DNA and DNA-manipulating enzymes that solves computational problems autonomously. The automaton's hardware consists of a restriction nuclease and ligase, the software and input are encoded by double-stranded DNA, and programming amounts to choosing appropriate software molecules. Upon mixing solutions containing these components, the automaton processes the input molecule via a cascade of restriction, hybridization and ligation cycles, producing a detectable output molecule that encodes the automaton's final state, and thus the computational result. In our implementation 1012 automata sharing the same software run independently and in parallel on inputs (which could, in principle, be distinct) in 120 microl solution at room temperature at a combined rate of 109 transitions per second with a transition fidelity greater than 99.8%, consuming less than 10-10 W. More... »

PAGES

430

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/35106533

DOI

http://dx.doi.org/10.1038/35106533

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1006789713

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/11719800


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