基于生物分子自动机的随机计算。
Stochastic computing with biomolecular automata.
作者信息
Adar Rivka, Benenson Yaakov, Linshiz Gregory, Rosner Amit, Tishby Naftali, Shapiro Ehud
机构信息
Department of Biological Chemistry, Weizmann Institute of Science, Rehovot 76100, Israel.
出版信息
Proc Natl Acad Sci U S A. 2004 Jul 6;101(27):9960-5. doi: 10.1073/pnas.0400731101. Epub 2004 Jun 23.
Abstract
Stochastic computing has a broad range of applications, yet electronic computers realize its basic step, stochastic choice between alternative computation paths, in a cumbersome way. Biomolecular computers use a different computational paradigm and hence afford novel designs. We constructed a stochastic molecular automaton in which stochastic choice is realized by means of competition between alternative biochemical pathways, and choice probabilities are programmed by the relative molar concentrations of the software molecules coding for the alternatives. Programmable and autonomous stochastic molecular automata have been shown to perform direct analysis of disease-related molecular indicators in vitro and may have the potential to provide in situ medical diagnosis and cure.
摘要
随机计算有广泛的应用，但电子计算机以一种繁琐的方式实现其基本步骤，即在不同的计算路径之间进行随机选择。生物分子计算机使用不同的计算范式，因此提供了新颖的设计。我们构建了一个随机分子自动机，其中随机选择是通过不同生化途径之间的竞争来实现的，选择概率由编码替代方案的软件分子的相对摩尔浓度编程。可编程和自主的随机分子自动机已被证明能够在体外对疾病相关分子指标进行直接分析，并且可能有潜力提供原位医学诊断和治疗。
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