Artificial neural networks have revolutionized electronic computing. Similarly, molecular
networks with neuromorphic architectures may enable molecular decision-making on a level …

This paper presents novel implementations for reservoir computing (RC) using DNA
oscillators. An RC system consists of two parts: reservoir and readout layer. The reservoir …

This paper is concerned with the utilization of deterministically modelled chemical reaction
networks for the implementation of (feed-forward) neural networks. We develop a general …

DNA-based neural networks are a type of DNA circuit capable of molecular pattern
recognition tasks. Winner-take-all DNA networks have been developed to scale up the …

DNA catalysts are fundamental building blocks for diverse molecular information-processing
circuits. Allosteric control of DNA catalysts has been developed to activate desired catalytic …

The design and implementation of adaptive chemical reaction networks, capable of
adjusting their behavior over time in response to experience, is a key goal for the fields of …

Artificial neural networks, inspired by the biological networks of the human brain, have
become game-changing computing models in modern computer science. Inspired by their …

Embedding computation in biochemical environments incompatible with traditional
electronics is expected to have a wide-ranging impact in synthetic biology, medicine …

Information processing relying on biochemical interactions in the cellular environment is
essential for biological organisms. The implementation of molecular computational systems …

Formal methods have enabled breakthroughs in many fields, such as in hardware
verification, machine learning and biological systems. The key object of interest in systems …