Composable Rate-Independent Computation in Continuous Chemical Reaction Networks
| Autor: | Wyatt Reeves, Niels Kornerup, Cameron T. Chalk, David Soloveichik |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
Superadditivity Biochemical Phenomena Computer science Computation 0206 medical engineering Computer Science - Emerging Technologies 02 engineering and technology Topology Composability Encoding (memory) Genetics Independence (probability theory) business.industry Applied Mathematics Construct (python library) Modular design Kinetics Emerging Technologies (cs.ET) Models Chemical Computer Science - Distributed Parallel and Cluster Computing Piecewise Synthetic Biology Distributed Parallel and Cluster Computing (cs.DC) business 020602 bioinformatics Biotechnology |
| Popis: | Biological regulatory networks depend upon chemical interactions to process information. Engineering such molecular computing systems is a major challenge for synthetic biology and related fields. The chemical reaction network (CRN) model idealizes chemical interactions, allowing rigorous reasoning about the computational power of chemical kinetics. Here we focus on function computation with CRNs, where we think of the initial concentrations of some species as the input and the equilibrium concentration of another species as the output. Specifically, we are concerned with CRNs that are rate-independent (the computation must be correct independent of the reaction rate law) and composable ($f\circ g$ can be computed by concatenating the CRNs computing $f$ and $g$). Rate independence and composability are important engineering desiderata, permitting implementations that violate mass-action kinetics, or even "well-mixedness", and allowing the systematic construction of complex computation via modular design. We show that to construct composable rate-independent CRNs, it is necessary and sufficient to ensure that the output species of a module is not a reactant in any reaction within the module. We then exactly characterize the functions computable by such CRNs as superadditive, positive-continuous, and piecewise rational linear. Thus composability severely limits rate-independent computation unless more sophisticated input/output encodings are used. Appeared at Computational Methods in Systems Biology (CMSB) 2018 (best paper award) To appear in IEEE/ACM Transactions on Computational Biology and Bioinformatics |
| Databáze: | OpenAIRE |
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