自组织反应网络中的化学储层计算

Wilhelm Huck, Mathieu Baltussen, Thijs de Jong, Quentin Duez, William Robinson
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引用次数: 0

摘要

信息的流动和能量的流动一样对生命至关重要。代谢和信号通路中的化学反应网络使细胞能够处理来自环境的信息3,4。目前分子信息处理和计算的方法通常追求数字计算范式,需要广泛的分子水平工程5。尽管取得了重大进展,但这些方法还没有达到生命系统中所见的信息处理能力水平。在这里,我们报告了一个基于福尔摩斯反应的化学储层计算机的发现和实现。我们展示了这个复杂的、自组织的化学反应网络如何并行地执行多个非线性分类任务,预测其他复杂系统的动态,以及时间序列预测。这在化学信息处理系统中为复杂化学反应网络的新兴计算能力提供了原理证明,为一类新的仿生信息处理系统铺平了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Chemical reservoir computation in a self-organizing reaction network
Abstract The flow of information is as crucial to life as the flow of energy1,2. Chemical reaction networks such as those found in metabolism and signalling pathways enable cells to process information from their environment3,4. Current approaches to molecular information processing and computation typically pursue digital computation paradigms and require extensive molecular-level engineering5. Despite significant advances, these approaches have not reached the level of information processing capabilities seen in living systems. Here, we report on the discovery and implementation of a chemical reservoir computer based on the formose reaction6. We demonstrate how this complex, self-organizing chemical reaction network can perform multiple non-linear classification tasks in parallel, of predicting the dynamics of other complex systems, and of time series forecasting. This in chemico information processing system provides proof-of-principle for the emergent computational capabilities of complex chemical reaction networks, paving the way for a new class of biomimetic information processing systems.
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