Natural systems are characterized by staggering complexities and behave with daunting dynamics. These complex interactions are performed by intertwined networks consisting of relatively simple components, like DNA, RNA and proteins. Living cells rely on the interplay of these molecular modules in order to collect information from the environment (inputs), perform signal transduction and translate them into a desired response by specialized actuators (outputs). [1] This intrinsically complex function, commonly referred as information processing or computation, is encountered across living and inanimate matter, on large (e.g. brain) or small scale (e.g. signaling pathways). Interestingly, computation processes that are able to integrate signals of ever-increasing complexity can be performed by simple and reusable building blocks, by following a uniform set of rules. [2]
Examples of biologically relevant models of computation, that are usually implemented, include state machines and logic circuits, however a number of computation models exploiting inherent characteristics of biomolecules have been created like splicing systems. [1] The assembly of molecular computers from interoperable parts, could revolutionize our ability to not only read or edit the genetic code, but also reprogram and repurpose it in order to systematically solve problems of large diversity.