Artificial neural networks provide a powerful paradigm for nonbiological information
processing. To understand whether similar principles could enable computation within living …

This work presents some ambitious perspectives on how Systems Chemistry can contribute
to developing the quite new research line of Chemical Artificial Intelligence (CAI). CAI refers …

Networks of chemical reactions exhibit emergent properties under out-of-equilibrium
conditions. Recent advances in systems chemistry demonstrate that networks with sufficient …

The construction of chemical reaction networks (CRNs) is a formidable challenge because
of their holistic and nonlinear nature. One approach to constructing CRNs involves …

A biological circuit is a neural or biochemical cascade, taking inputs and producing outputs.
How have biological circuits learned to solve environmental challenges over the history of …

This study explores the use of bacterial strains in reservoir computing (RC) to solve
regression and classification tasks. We employ an Escherichia coli K-12 MG1655 strain as …

The ambition to relate intrinsic features of chemical data to the underlying chemical reaction
networks (CRNs) is not new, but has experienced only modest success. This may partly be …

Exploring the chemical space of prebiotic reactions is crucial for understanding the
emergence of life. However, the combinatorial explosion of compounds and the lack of user …