Synthesizing and Tuning Chemical Reaction Networks with Specified Behaviours

  • Neil Dalchau
  • Niall Murphy
  • Rasmus Petersen
  • Boyan Yordanov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9211)


We consider how to generate chemical reaction networks (CRNs) from functional specifications. We propose a two-stage approach that combines synthesis by satisfiability modulo theories and Markov chain Monte Carlo based optimisation. First, we identify candidate CRNs that have the possibility to produce correct computations for a given finite set of inputs. We then optimise the reaction rates of each CRN using a combination of stochastic search techniques applied to the chemical master equation, simultaneously improving the probability of correct behaviour and ruling out spurious solutions. In addition, we use techniques from continuous time Markov chain theory to study the expected termination time for each CRN. We illustrate our approach by identifying CRNs for majority decision-making and division computation, which includes the identification of both known and unknown networks.


Chemical reaction networks Program synthesis Parameter optimisation Chemical master equation Satisfiability modulo theories Markov chain Monte Carlo 



We thank Dan Alistarh and Luca Cardelli for helpful discussions on the development and applications of our methodology.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Neil Dalchau
    • 1
  • Niall Murphy
    • 1
  • Rasmus Petersen
    • 1
  • Boyan Yordanov
    • 1
  1. 1.Microsoft ResearchCambridgeUK

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