Abstract
In the context of possibilistic decision making, this work deals with biological design problems particularly important in the near future when it will be possible to produce biological entities and synthetic organisms for pharmacological and medical usage. The biological systems is investigated in terms of performances or main key features of the system. The analysis of the biological system is based on the idea that the set of parameters involved in the model can be classified into two different typologies: the uncertain kinetic parameters and the control design parameters. In order to design a robust and reliable biological system with respect to a target performance, the design parameter values are set up to balance the uncertainty of the kinetic parameters. To take into account these uncertainties arising from the estimations of the kinetic parameters, the function representing the feedback of the system is fuzzified and a measure of failure of the designed biological circuit is minimized to reach the required performance. An application of this methodology is illustrated on a case study of an autonomously oscillatory system: the Drosophila Period Protein which is a central component of the Drosophila circadian clocks. Finally, the results of the fuzzy methodology are compared with a deterministic method.
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Sciacca, E., Spinella, S. (2010). Reliable Biological Circuit Design Including Uncertain Kinetic Parameters. In: Lodwick, W.A., Kacprzyk, J. (eds) Fuzzy Optimization. Studies in Fuzziness and Soft Computing, vol 254. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13935-2_21
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DOI: https://doi.org/10.1007/978-3-642-13935-2_21
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