Learning is traditionally studied in biological or computational systems. The power of
learning frameworks in solving hard inverse problems provides an appealing case for the …

Synthetic biology uses living cells as the substrate for performing human-defined
computations. Many current implementations of cellular computing are based on the …

Biological organisms use complex molecular networks to navigate their environment and
regulate their internal state. The development of synthetic systems with similar capabilities …

Molecular programming aims to systematically engineer molecular and chemical systems of
autonomous function and ever-increasing complexity. A key goal is to develop embedded …

We build a rigorous nonequilibrium thermodynamic description for open chemical reaction
networks of elementary reactions. Their dynamics is described by deterministic rate …

Signal processing over the molecular domain is critical for analysing, modifying, and
synthesising chemical signals in molecular communication systems. However, the lack of …

One of the central concerns of computer science is how the resources needed to perform a
given computation depend on that computation. Moreover, one of the major resource …

Life is confronted with computation problems in a variety of domains including animal
behavior, single-cell behavior, and embryonic development. Yet we currently do not know of …

DNA circuits have been widely used to develop biological computing devices because of
their high programmability and versatility. Here, we propose an architecture for the …

Chemical reaction networks (CRNs) formally model chemistry in a well-mixed solution.
CRNs are widely used to describe information processing occurring in natural cellular …