ArticleEvolutionary bioinformatics online2013
Design of synthetic genetic oscillators using evolutionary optimization.
Article in Evolutionary bioinformatics online, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- GCAD: A Computational Framework for Mammalian Genetic Program Computer-Aided Design.ACS synthetic biology · 2026Article
- GCAD: a Computational Framework for Mammalian Genetic Program Computer-Aided Design.bioRxiv : the preprint server for biology · 2025Article
- Article
- Synthesis of control unit for future biocomputer.Journal of biological engineering · 2018Article
- Designing synthetic networks in silico: a generalised evolutionary algorithm approach.BMC systems biology · 2017Article
- Toward theoretical synthesis of biocomputer.IET systems biology · 2017Article
- Synthesising gene clock with toggle switch and oscillator.IET systems biology · 2015Article
- Synthesizing genetic sequential logic circuit with clock pulse generator.BMC systems biology · 2014Article
- Synthesising periodic triggering signals with genetic oscillators.IET systems biology · 2014Article
- Systematic design methodology for robust genetic transistors based on I/O specifications via promoter-RBS libraries.BMC systems biology · 2013Article
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3 authors.
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Abstract
Efforts have been made to establish computer models of genetic oscillation. We have developed a real structured genetic algorithm (RSGA) which combines advantages of the traditional real genetic algorithm (RGA) with those of the structured genetic algorithm (SGA) and applies it as an optimization strategy for genetic oscillator design. For the generalized design, our proposed approach fulfils all types of genes by minimizing the order of oscillator while searching for the optimal network parameters. The design approach is shown to be capable of yielding genetic oscillators with a simpler structure while possessing satisfactory oscillating behavior. In silico experiments show effectiveness of the proposed algorithm to genetic oscillator design. In particular, it is shown that the proposed approach performs better than the traditional GAs in the sense that a cheaper structure of genetic oscillators can be obtained.
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