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Molecular Algorithms Using Reprogrammable DNA Self-assembly

机译:使用可重编程DNA自组装的分子算法

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The history of computing tells us that computers can be made of almost anything: silicon, gears and levers, neurons, flowing water, interacting particles or even light. Although lithographically patterned silicon surfaces have been by far the most successful of these, they give us a limited view of what computation is capable of. Algorithms typically control the flow of information by controlling the flow of electrons through digital-electronic devices, but in the field of molecular computing we imagine algorithms that control matter itself.This talk will be about DNA molecules that interact with each other in a test tube to execute algorithms. We will show how DNA can be re-engineered to act not only as an information encoding polymer (as it is in biology) but also as a computational primitive for executing somewhat soggy computer programs. The talk will showcase some of our wet-lab results on implementing 21 different algorithms using self-assembling DNA strands |1]. We will also see how tools from the theory of computation can help us understand what kinds of computations molecules are capable of.[1] Woods*, Doty*. Myhrvold, Hui, Zhou, Yin, Winfree. Diverse and robust molecular algorithms using reprogrammable DNA self-assembly. Nature 567:366-372. 2019. *Joint lead co-authors.
机译:计算的历史告诉我们,计算机几乎可以由任何东西组成:硅,齿轮和杠杆,神经元,流动的水,相互作用的粒子甚至是光。尽管光刻图形化的硅表面迄今为止是最成功的表面,但它们使我们对计算能力的看法有限。算法通常通过控制电子流过数字电子设备的方式来控制信息流,但是在分子计算领域,我们想象的是控制物质本身的算法。本文将讨论在试管中相互作用的DNA分子。执行算法。我们将展示如何重新设计DNA,以不仅充当信息编码聚合物(就像在生物学中一样),而且还充当执行某些潮湿计算机程序的计算原语。演讲将展示我们在使用自组装DNA链实现21种不同算法方面的一些湿实验室结果[1]。我们还将看到计算理论中的工具如何帮助我们理解分子能够进行哪种计算。[1]伍兹*,道蒂*。 Myhrvold,Hui,Zhou,Yin,Winfree。使用可重编程的DNA自组装的多样而强大的分子算法。自然567:366-372。 2019年。*联合首席作者。

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