Chemical Reaction Network

Chemical reaction networks (CRNs) model the interactions of molecules, providing a framework to understand and engineer complex biochemical systems. Current research focuses on developing and applying CRN models for computation, including using them to implement machine learning algorithms like neural networks and to efficiently simulate large-scale systems like those found in astrochemistry. These advancements are driving progress in synthetic biology, enabling the design of autonomous biochemical systems for applications such as diagnostics and therapeutics, and also improving the accuracy and speed of simulations in diverse fields. Furthermore, research is exploring the theoretical connections between CRNs and other computational models, leading to a deeper understanding of self-organization and computation in both natural and artificial systems.