Chemical reaction networks for computing logarithm.
Chemical reaction networks for computing logarithm.
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DOI：
10.1093/synbio/ysx002
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发表时间：
2017-01
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影响因子：
--
通讯作者：
Chou CT
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文献类型：
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作者：
Chou CT
活细胞不断地处理来自其生活环境的信息。最近的研究表明，许多细胞信号机制(如G蛋白偶联受体和表皮生长因子)可以解释为计算配体浓度的对数。这表明对数是细胞中的基本计算原语。合成生物界对实现模拟计算也越来越感兴趣，计算对数就是这样一个例子。本文的目的是研究如何利用化学反应网络(CRN)实现对数的计算。CRN不能准确地计算对数。一种标准的方法是使用幂函数或有理函数近似来近似计算对数。虽然CRN可以以一种简单的方式实现这些多项式或有理函数的计算，但问题是为了能够在大的输入范围内准确地计算对数，有必要使用导致CRN具有大量反应的高阶近似。本文提出了一种新的方法来精确地计算CRN中的对数，同时保持CRN中的反应数目较少。该方法通过调整两个设计参数，可以生成计算不同精度对数的CRN。在这篇文章中，我们介绍了实现CRN计算对数所需的化学反应。本文的主要贡献是一种创建CRN的新方法，该方法只使用少量的化学反应就可以在很大的输入范围内准确地计算对数。
Living cells constantly process information from their living environment. It has recently been shown that a number of cell signaling mechanisms (e.g. G protein-coupled receptor and epidermal growth factor) can be interpreted as computing the logarithm of the ligand concentration. This suggests that logarithm is a fundamental computation primitive in cells. There is also an increasing interest in the synthetic biology community to implement analog computation and computing the logarithm is one such example. The aim of this article is to study how the computation of logarithm can be realized using chemical reaction networks (CRNs). CRNs cannot compute logarithm exactly. A standard method is to use power series or rational function approximation to compute logarithm approximately. Although CRNs can realize these polynomial or rational function computations in a straightforward manner, the issue is that in order to be able to compute logarithm accurately over a large input range, it is necessary to use high-order approximation that results in CRNs with a large number of reactions. This article proposes a novel method to compute logarithm accurately in CRNs while keeping the number of reactions in CRNs low. The proposed method can create CRNs that can compute logarithm to different levels of accuracy by adjusting two design parameters. In this article, we present the chemical reactions required to realize the CRNs for computing logarithm. The key contribution of this article is a novel method to create CRNs that can compute logarithm accurately over a wide input range using only a small number of chemical reactions.