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DNA Computation: Theory, Practice, and Prospects

机译:DNA计算:理论,实践和展望

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L. M. Adleman launched the field of DNA computing with a demonstration in 1994 that strands of DNA could be used to solve the Hamiltonian path problem for a simple graph. He also identified three broad categories of open questions for the field. First, is DNA capable of universal computation? Second, what kinds of algorithms can DNA implement? Third, can the error rates in the manipulations of the DNA be controlled enough to allow for useful computation? In the two years that have followed, theoretical work has shown that DNA is in fact capable of universal computation. Furthermore, algorithms for solving interesting questions, like breaking the Data Encryption Standard, have been described using currently available technology and methods. Finally, a few algorithms have been proposed to handle some of the apparently crippling error rates in a few of the common processes used to manipulate DNA. It is thus unlikely that DNA computation is doomed to be only a passing curiosity. However, much work remains to be done on the containment and correction of errors. It is far from clear if the problems in the error rates can be solved sufficiently to ever allow for general-purpose computation that will challenge the more popular substrates for computation. Unfortunately, biological demonstrations of the theoretical results have been sadly lacking. To date, only the simplest of computations have been carried out in DNA. To make significant progress, the field will require both the assessment of the practicality of the different manipulations of DNA and the implementation of algorithms for realistic problems. Theoreticians, in collaboration with experimentalists, can contribute to this research program by settling on a small set of practical and efficient models for DNA computation.
机译:L. M. Adleman在1994年进行了一次演示,展示了DNA链可用于解决简单图形的汉密尔顿路径问题的研究,从而启动了DNA计算领域。他还为该领域确定了三大类公开问题。首先,DNA是否具有通用计算能力?其次,DNA可以实现哪种算法?第三,是否可以控制DNA操作中的错误率以进行有用的计算?在随后的两年中,理论工作表明DNA实际上具有通用计算能力。此外,已经使用当前可用的技术和方法描述了用于解决有趣的问题的算法,例如破坏数据加密标准。最后,已经提出了一些算法来处理一些用于操纵DNA的常见过程中的一些明显的错误率。因此,DNA计算注定不会只是一时的好奇心。但是,在遏制和纠正错误方面仍有许多工作要做。能否充分解决错误率中的问题还远远不能解决,以至于无法进行通用计算,而通用计算将挑战更流行的计算基板。不幸的是,令人遗憾的是缺乏理论结果的生物学证明。迄今为止,在DNA中仅进行了最简单的计算。为了取得重大进展,该领域既需要评估DNA的不同操作的实用性,也需要实施针对实际问题的算法。理论家与实验家合作,可以通过建立一套实用而有效的DNA计算模型来为这一研究计划做出贡献。

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