The construction of an artificial biological logic circuit using systematic strategy is recognised as one of the most important topics for the development of synthetic biology. In this study, a real-structured genetic algorithm (RSGA), which combines general advantages of the traditional real genetic algorithm with those of the structured genetic algorithm, is proposed to deal with the biological logic circuit design problem. A general model with the cis-regulatory input function and appropriate promoter activity functions is proposed to synthesise a wide variety of fundamental logic gates such as NOT, Buffer, AND, OR, NAND, NOR and XOR. The results obtained can be extended to synthesise advanced combinational and sequential logic circuits by topologically distinct connections. The resulting optimal design of these logic gates and circuits are established via the RSGA. The in silico computer-based modelling technology has been verified showing its great advantages in the purpose.

Stochastic modelling of coupled Ca²⁺ channels is a challenge, especially when the coupling of the channels, as determined by their spatial arrangement relative to each other, has to be considered at multiple spatial scales. In this study, the authors address this problem using coloured stochastic Petri nets (𝒮𝒫𝒩^𝒸) as high-level description to generate continuous-time Markov chains. The authors develop several models with increasing complexity. They first apply 𝒮𝒫𝒩^𝒸 to model single clusters of coupled Ca²⁺ channels arranged in a regular or irregular lattice, where they describe how to represent the geometrical arrangement of Ca²⁺ channels relative to each other using colours. They then apply this modelling idea to construct more complex models by modelling spatially arranged clusters of channels. The authors’ models can be easily reproduced and adapted to different scenarios.

DNA mismatch repair (MMR) is involved in processing DNA damage following treatment with ionising radiation (IR) and various classes of chemotherapy drugs including iododeoxyuridine (IUdR), a known radiosensitiser. In this study, the authors have developed asynchronous probabilistic cell cycle models to assess the isolated effects of IUdR and IR and the combined effects of IUdR + IR treatments on MMR damage processing. The authors used both synchronous and asynchronous MMR-proficient/MMR-deficient cell populations and followed treated cells for up to two cell cycle times. They have observed and quantified differential cell cycle responses to MMR damage processing following IR and IUdR + IR treatments, principally in the duration of both G1 and G2/M cell cycle phases. The models presented in this work form the foundation for the development of an approach to maximise the therapeutic index for IR and IUdR + IR treatments in MMR-deficient (damage tolerant) cancers.