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1. Reactamole: Functional Reactive Molecular Programming

   Klinge, Titus H.; Lathrop, James I.; Osera, Peter-Michael; Rogers, Allison (January 2021, 27th International Conference on DNA Computing and Molecular Programming (DNA 27))

   Lakin, Matthew R.; Šulc, Petr (Ed.)

   Chemical reaction networks (CRNs) are an important tool for molecular programming, a field that is rapidly expanding our ability to deploy computer programs into biological systems for a variety of applications. However, CRNs are also difficult to work with due to their massively parallel nature, leading to the need for higher-level languages that allow for easier computation with CRNs. Recently, research has been conducted into a variety of higher-level languages for deterministic CRNs but modeling CRN parallelism, managing error accumulation, and finding natural CRN representations are ongoing challenges. We introduce Reactamole, a higher-level language for deterministic CRNs that utilizes the functional reactive programming (FRP) paradigm to represent CRNs as a reactive dataflow network. Reactamole equates a CRN with a functional reactive program, implementing the key primitives of the FRP paradigm directly as CRNs. The functional nature of Reactamole makes reasoning about molecular programs easier, and its strong static typing allows us to ensure that a CRN is well-formed by virtue of being well-typed. In this paper, we describe the design of Reactamole and how we use CRNs to represent the common datatypes and operations found in FRP. We also demonstrate the potential of this functional reactive approach to molecular programming by giving an extended example where a CRN is constructed using FRP to modulate and demodulate an amplitude modulated signal. 

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2. Reactamole: functional reactive molecular programming

   https://doi.org/10.1007/s11047-024-09982-5  

   Klinge, Titus H; Lathrop, James I; Osera, Peter-Michael; Rogers, Allison (April 2024, Natural Computing)

   Chemical reaction networks (CRNs) are an important tool for molecular programming. This field is rapidly expanding our ability to deploy computer programs into biological systems for various applications. However, CRNs are also difficult to work with due to their massively parallel nature, leading to the need for higher-level languages that allow for more straightforward computation with CRNs. Recently, research has been conducted into various higher-level languages for deterministic CRNs but modeling CRN parallelism, managing error accumulation, and finding natural CRN representations are ongoing challenges. We introduce Reactamole, a higher-level language for deterministic CRNs that utilizes the functional reactive programming (FRP) paradigm to represent CRNs as a reactive dataflow network. Reactamole equates a CRN with a functional reactive program, implementing the key primitives of the FRP paradigm directly as CRNs. The functional nature of Reactamole makes reasoning about molecular programs easier, and its strong static typing allows us to ensure that a CRN is well-formed by virtue of being well-typed. In this paper, we describe the design of Reactamole and how we use CRNs to represent the common datatypes and operations found in FRP. We demonstrate the potential of this functional reactive approach to molecular programming by giving an extended example where a CRN is constructed using FRP to modulate and demodulate an amplitude-modulated signal. We also show how Reactamole can be used to specify abstract CRNs whose structure depends on the reactions and species of its input, allowing users to specify more general CRN behaviors. 

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3. Computing Threshold Circuits with Bimolecular Void Reactions in Step Chemical Reaction Networks

   Anderson, Rachel; Fu, Bin; Massie, Aiden; Mukhopadhyay, Gourab; Salinas, Adrian; Schweller, Robert; Tomai, Evan; Wylie, Tim (June 2024, Springer Nature)

   Step Chemical Reaction Networks (step CRNs) are an augmentation of the Chemical Reaction Network (CRN) model where additional species may be introduced to the system in a sequence of “steps.” We study step CRN systems using a weak subset of reaction rules, void rules, in which molecular species can only be deleted. We demonstrate that step CRNs with only void rules of size (2,0) can simulate threshold formulas (TFs) under linear resources. These limited systems can also simulate threshold circuits (TCs) by modifying the volume of the system to be exponential. We then prove a matching exponential lower bound on the required volume for simulating threshold circuits in a step CRN with (2,0)-size rules under a restricted gate-wise simulation, thus showing our construction is optimal for simulating circuits in this way. 

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4. A Framework for Testing Chemical Reaction Networks

   https://doi.org/10.1145/3551349.3559562  

   Gerten, Michael C. (October 2022, 37th IEEE/ACM International Conference on Automated Software Engineering (ASE '22) Doctoral Symposium)

   The use of non-traditional computing devices is growing rapidly. One paradigm of interest is chemical reaction networks (CRNs) which can model and use chemical interactions for computation. These CRNs are used to develop programs at the nanoscale for applications such as intelligent drug delivery. In practice, these programs are developed in simulation environments, and then compiled into physical systems. A challenge when designing CRNs for computation is the lack of techniques to verify and validate correctness. In this work, we adapt software testing and repair techniques for use in this domain. In initial work, we designed a testing framework to handle the challenges presented by CRN programs; this includes distributed computation and stochastic behavior. We extended this framework to implement automated program repair of CRN models and automated test generation via program invariants. For future work, we will develop a notion of fault localization for these programs, develop a theory of mutation generation, and address issues regarding flakiness present in this computing paradigm. 

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5. Composable Rate-Independent Computation in Continuous Chemical Reaction Networks

   https://doi.org/10.1007/978-3-319-99429-1_15  

   Chalk, C; Kornerup, N; Reeves, W; Soloveichik, D (January 2018, Computational Methods in Systems Biology. CMSB 2018.)

   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, abstracting away specifics of the molecular implementation, and 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 eventual steady-state 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∘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. Our results show that composability severely limits rate-independent computation unless more sophisticated input/output encodings are used. 

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