conventional biochemical extraction methods Adelman was able to isolate only

Conventional biochemical extraction methods adelman

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conventional biochemical extraction methods, Adelman was able to isolate onlyDNA   nanostructures   encoding   Hamiltonian   paths,   and   by   determining   theirsequence,   the   explicit   Hamiltonian   path.   It   should   be   mentioned   that   thislandmark   experiment   was   designed   and   experimentally   demonstrated   byAdleman alone, a computer scientist with limited training in biochemistry.3.2 The Non-Scalability of Adelman’s ExperimentWhile this experiment founded the field of DNA computing, it was not scalable inpractice,   since   the   number   of   different   DNA   strands   needed   increasedexponentially with the number of nodes of the graph. Although there can be an13
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enormous number of DNA strands in a test tube (1015  or more, depending onsolution concentration), the size of the largest graph that could be solved by hismethod was limited to at most a few dozen nodes. This is not surprising, sincefinding the Hamiltonian path is an NP complete problem, whose solution is likelyto be intractable using conventional computers. Even though DNA computersoperate   at   the   molecular-scale,   they   are   still   equivalent   to   conventionalcomputers (e.g., deterministic Turing machines) in computational power. Thisexperiment taught a healthy lesson to the DNA computing community (which isnow well-recognized): to carefully examine scalability issues and to judge anyproposed experimental methodology by its scalability.3.3 Autonomous Biomolecular ComputationShortly following Adleman‘s experiment, there was a burst of further experimentsin DNA computing, many of which were quite ingenious. However, almost noneof these DNA computing methods were autonomous, and instead required manytedious   laboratory   steps  to   execute.  In   retrospect,   one   of  the   most  notableaspects   of  Adleman’s   experiment   was   that   the   self-assembly   phase   of   theexperiment was completely autonomous - it required no exterior mediation (thebulk of the labor was in the non-autonomous molecular sorting steps). Thestrategy can be termed generate-and-sort, since all possible answers are createdand   incorrect   solutions   are   subsequently   discarded.   Maximizing   molecular14
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autonomy makes an experimental laboratory demonstration much more feasibleas the scale increases. The remaining article mostly discusses autonomousdevices for bio-molecular computation based on self-assembly.
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  • Spring '14
  • ALANNASCHEPARTZ
  • DNA, Molecule, DNA nanostructures

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