发帖
雷达卡
摘要翻译：
我们报告了一个生化与门的“输入输出面”的实验评估。所获得的数据在速率方程方法中建模，目的是映射出门函数，并将其转换为适合布尔逻辑分析的逻辑变量语言，以提高可伸缩性。为了使“模拟”噪声最小化，我们考虑了一种理论方法来确定工艺参数的最佳集，以使门级联的“模拟”噪声放大最小化。我们确定，在优化的条件下，目前研究的生化门可串联多达10个加工步骤。除此之外，还必须开发新的模式来避免噪音的积累。我们对推进可扩展生化计算的实验和理论研究的思路和未来可能面临的挑战进行了一般性的讨论。
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英文标题：
《Optimization of Enzymatic Biochemical Logic for Noise Reduction and
Scalability: How Many Biocomputing Gates Can Be Interconnected in a Circuit?》
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作者：
V. Privman, G. Strack, D. Solenov, M. Pita, E. Katz
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最新提交年份：
2008
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分类信息：
一级分类：Quantitative Biology 数量生物学
二级分类：Molecular Networks 分子网络
分类描述：Gene regulation, signal transduction, proteomics, metabolomics, gene and enzymatic networks
基因调控、信号转导、蛋白质组学、代谢组学、基因和酶网络
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一级分类：Physics 物理学
二级分类：Other Condensed Matter 其他凝聚态物质
分类描述：Work in condensed matter that does not fit into the other cond-mat classifications
在不适合其他cond-mat分类的凝聚态物质中工作
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一级分类：Physics 物理学
二级分类：Soft Condensed Matter 软凝聚态物质
分类描述：Membranes, polymers, liquid crystals, glasses, colloids, granular matter
膜，聚合物，液晶，玻璃，胶体，颗粒物质
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一级分类：Computer Science 计算机科学
二级分类：Computational Complexity 计算复杂度
分类描述：Covers models of computation, complexity classes, structural complexity, complexity tradeoffs, upper and lower bounds. Roughly includes material in ACM Subject Classes F.1 (computation by abstract devices), F.2.3 (tradeoffs among complexity measures), and F.4.3 (formal languages), although some material in formal languages may be more appropriate for Logic in Computer Science. Some material in F.2.1 and F.2.2, may also be appropriate here, but is more likely to have Data Structures and Algorithms as the primary subject area.
涵盖计算模型，复杂度类别，结构复杂度，复杂度折衷，上限和下限。大致包括ACM学科类F.1（抽象设备的计算）、F.2.3（复杂性度量之间的权衡）和F.4.3（形式语言）中的材料，尽管形式语言中的一些材料可能更适合于计算机科学中的逻辑。在F.2.1和F.2.2中的一些材料可能也适用于这里，但更有可能以数据结构和算法作为主要主题领域。
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一级分类：Quantitative Biology 数量生物学
二级分类：Biomolecules 生物分子
分类描述：DNA, RNA, proteins, lipids, etc.; molecular structures and folding kinetics; molecular interactions; single-molecule manipulation.
DNA、RNA、蛋白质、脂类等；分子结构与折叠动力学；分子相互作用；单分子操作。
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一级分类：Quantitative Biology 数量生物学
二级分类：Other Quantitative Biology 其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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一级分类：Quantitative Biology 数量生物学
二级分类：Quantitative Methods 定量方法
分类描述：All experimental, numerical, statistical and mathematical contributions of value to biology
对生物学价值的所有实验、数值、统计和数学贡献
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一级分类：Physics 物理学
二级分类：Quantum Physics 量子物理学
分类描述：Description coming soon
描述即将到来
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英文摘要：
We report an experimental evaluation of the "input-output surface" for a biochemical AND gate. The obtained data are modeled within the rate-equation approach, with the aim to map out the gate function and cast it in the language of logic variables appropriate for analysis of Boolean logic for scalability. In order to minimize "analog" noise, we consider a theoretical approach for determining an optimal set for the process parameters to minimize "analog" noise amplification for gate concatenation. We establish that under optimized conditions, presently studied biochemical gates can be concatenated for up to order 10 processing steps. Beyond that, new paradigms for avoiding noise build-up will have to be developed. We offer a general discussion of the ideas and possible future challenges for both experimental and theoretical research for advancing scalable biochemical computing.
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PDF链接：
https://arxiv.org/pdf/0803.4197
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