Metabolic perceptrons for neural computing in biological systems

So far, synthetic genetic circuits have relied on digital logic for information processing. Here the authors present metabolic perceptrons that use analog weighted adders to vary the contributions of multiple inputs, resulting in different classification functions.

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Bibliographic Details
Main Authors: Amir Pandi, Mathilde Koch, Peter L. Voyvodic, Paul Soudier, Jerome Bonnet, Manish Kushwaha, Jean-Loup Faulon
Format: article
Language:EN
Published: Nature Portfolio 2019
Subjects:
Q
Online Access:https://doaj.org/article/5f0e78829b1940c1802523d6a5e44de7
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Description
Summary:So far, synthetic genetic circuits have relied on digital logic for information processing. Here the authors present metabolic perceptrons that use analog weighted adders to vary the contributions of multiple inputs, resulting in different classification functions.