Stably computable predicates are semilinear
Proceedings of the twenty-fifth annual ACM symposium on Principles of distributed computing
Computation with finite stochastic chemical reaction networks
Natural Computing: an international journal
Strand algebras for DNA computing
Natural Computing: an international journal
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Understanding the algorithmic behaviors that are in principle realizable in a chemical system is necessary for a rigorous understanding of the design principles of biological regulatory networks. Further, advances in synthetic biology herald the time when we'll be able to rationally engineer complex chemical systems, and when idealized formal models will become blueprints for engineering. Coupled chemical interactions in a well-mixed solution are commonly formalized as chemical reaction networks (CRNs). However, despite the widespread use of CRNs in the natural sciences, the range of computational behaviors exhibited by CRNs is not well understood. Here we study the following problem: what functions f : ∪k → ∪ can be computed by a chemical reaction network, in which the CRN eventually produces the correct amount of the "output" ∣ molecule, no matter the rate at which reactions proceed? This captures a previously unexplored, but very natural class of computations: for example, the reaction X1 + X2 → Y can be thought to compute the function y = min(x1, x2). Such a CRN is robust in the sense that it is correct whether its evolution is governed by the standard model of mass-action kinetics, alternatives such as Hill-function or Michaelis-Menten kinetics, or other arbitrary models of chemistry that respect the (fundamentally digital) stoichiometric constraints (what are the reactants and products?). We develop a formal definition of such computation using a novel notion of reachability, and prove that a function is computable in this manner if and only if it is continuous piecewise linear.