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Chemical reservoir computation in a self-organizing reaction network.

Mathieu G BaltussenThijs J de JongQuentin DuezWilliam E RobinsonWilhelm T S Huck
Published in: Nature (2024)
Chemical reaction networks, such as those found in metabolism and signalling pathways, enable cells to process information from their environment 1,2 . Current approaches to molecular information processing and computation typically pursue digital computation models and require extensive molecular-level engineering 3 . Despite considerable 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 reaction 4 . We demonstrate how this complex, self-organizing chemical reaction network can perform several nonlinear classification tasks in parallel, predict the dynamics of other complex systems and achieve 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.
Keyphrases
  • health information
  • deep learning
  • primary care
  • induced apoptosis
  • machine learning
  • small molecule
  • electron transfer
  • working memory
  • single molecule
  • endoplasmic reticulum stress
  • single cell