Biomolecular computing (BMC) aims to capture the innumerable advantages that biological molecules have gained in the course of millions of years of evolution to perform computation unfeasible on conventional electronic computers. While biomolecules have resolved fundamental problems as a parallel computer system that we are just beginning to decipher, BMC still suffers from our inability to harness these properties to bring biomolecular computations to levels of reliability, efficiency and scalability that are now taken for granted with conventional solid-state based computers. Here, we explore an alternative approach to exploiting these properties by building virtual test tubes in software that would capture the fundamental advantages of biomolecules, in the same way that evolutionary algorithms capture in silico the key properties of Darwinian evolution. We use a previously built tool, Edna , to explore the capabilities of the new paradigm.
Max H. Garzon, Evan Drumwright, Russell J. Deaton,