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Multicellular artificial neural network-type architectures demonstrate computational problem solving
Nature Chemical Biology ( IF 12.9 ) Pub Date : 2024-09-16 , DOI: 10.1038/s41589-024-01711-4
Deepro Bonnerjee, Saswata Chakraborty, Biyas Mukherjee, Ritwika Basu, Abhishek Paul, Sangram Bagh

Here, we report a modular multicellular system created by mixing and matching discrete engineered bacterial cells. This system can be designed to solve multiple computational decision problems. The modular system is based on a set of engineered bacteria that are modeled as an ‘artificial neurosynapse’ that, in a coculture, formed a single-layer artificial neural network-type architecture that can perform computational tasks. As a demonstration, we constructed devices that function as a full subtractor and a full adder. The system is also capable of solving problems such as determining if a number between 0 and 9 is a prime number and if a letter between A and L is a vowel. Finally, we built a system that determines the maximum number of pieces of a pie that can be made for a given number of straight cuts. This work may have importance in biocomputer technology development and multicellular synthetic biology.



中文翻译:


多细胞人工神经网络类型架构展示了计算问题解决方案



在这里,我们报告了一个通过混合和匹配离散工程细菌细胞创建的模块化多细胞系统。该系统可以设计为解决多个计算决策问题。该模块化系统基于一组工程细菌,这些细菌被建模为“人工神经突触”,在共培养中,形成了可以执行计算任务的单层人工神经网络型架构。作为演示,我们构建了用作全减法器和全加法器的设备。该系统还能够解决诸如确定 0 到 9 之间的数字是否为素数以及 A 和 L 之间的字母是否为元音等问题。最后,我们构建了一个系统,用于确定给定数量的直线切割可以制作的馅饼的最大块数。这项工作可能在生物计算机技术开发和多细胞合成生物学中具有重要意义。

更新日期:2024-09-16
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