ArticleBioinformatics (Oxford, England)2009
Robust synthetic biology design: stochastic game theory approach.
Article in Bioinformatics (Oxford, England), 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Article
- Article
- Using Nonlinear Stochastic Evolutionary Game Strategy to Model an Evolutionary Biological Network of Organ Carcinogenesis Under a Natural Selection Scheme.Evolutionary bioinformatics online · 2015Article
- The stochastic evolutionary game for a population of biological networks under natural selection.Evolutionary bioinformatics online · 2014Article
- Article
- A computational pipeline for identifying kinetic motifs to aid in the design and improvement of synthetic gene circuits.BMC bioinformatics · 2013Article
- A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-offs on Phenotype Robustness in Biological Networks. Part III: Synthetic Gene Networks in Synthetic Biology.Evolutionary bioinformatics online · 2013Article
- The new biology: a bridge to clinical cardiology.Hippokratia · 2012Article
- BSim: an agent-based tool for modeling bacterial populations in systems and synthetic biology.PloS one · 2012Article
- On the Interplay between the Evolvability and Network Robustness in an Evolutionary Biological Network: A Systems Biology Approach.Evolutionary bioinformatics online · 2011Article
- Robust design of biological circuits: evolutionary systems biology approach.Journal of biomedicine & biotechnology · 2011Article
- GA-based Design Algorithms for the Robust Synthetic Genetic Oscillators with Prescribed Amplitude, Period and Phase.Gene regulation and systems biology · 2010Article
- The challenges of informatics in synthetic biology: from biomolecular networks to artificial organisms.Briefings in bioinformatics · 2010Review
- A systematic design method for robust synthetic biology to satisfy design specifications.BMC systems biology · 2009Article
- Computer-aided design of biological circuits using TinkerCell.Bioengineered bugsArticle
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3 authors.
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Abstract
motivationSynthetic biology is to engineer artificial biological systems to investigate natural biological phenomena and for a variety of applications. However, the development of synthetic gene networks is still difficult and most newly created gene networks are non-functioning due to uncertain initial conditions and disturbances of extra-cellular environments on the host cell. At present, how to design a robust synthetic gene network to work properly under these uncertain factors is the most important topic of synthetic biology.
resultsA robust regulation design is proposed for a stochastic synthetic gene network to achieve the prescribed steady states under these uncertain factors from the minimax regulation perspective. This minimax regulation design problem can be transformed to an equivalent stochastic game problem. Since it is not easy to solve the robust regulation design problem of synthetic gene networks by non-linear stochastic game method directly, the Takagi-Sugeno (T-S) fuzzy model is proposed to approximate the non-linear synthetic gene network via the linear matrix inequality (LMI) technique through the Robust Control Toolbox in Matlab. Finally, an in silico example is given to illustrate the design procedure and to confirm the efficiency and efficacy of the proposed robust gene design method. AVAILABILITY: http://www.ee.nthu.edu.tw/bschen/SyntheticBioDesign_supplement.pdf.
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