Effective sampling trajectory optimisation for sensitivity analysis of biological systems |
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| Authors: | Zhao Z. Xu Ji Liu |
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| Affiliation: | 1. College of Information Science and Engineering, Key Laboratory of Advanced Control and Optimisation for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237 People''s Republic of China |
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| Abstract: | Sensitivity analysis has been widely applied to study the biological systems, including metabolic networks, signalling pathways, and genetic circuits. The Morris method is a kind of screening sensitivity analysis approach, which can fast identify a few key factors from numerous biological parameters and inputs. The parameter or input space is randomly sampled to produce a very limited number of trajectories for the calculation of elementary effects. It is clear that the sampled trajectories are not enough to cover the whole uncertain space, which eventually causes unstable sensitivity measures. This paper presents a novel trajectory optimisation algorithm for the Morris‐based sensitivity calculation to ensure a good scan throughout the whole uncertain space. The paper demonstrates that this presented method gets more consistent sensitivity results through a benchmark example. The application to a previously published ordinary differential equation model of a cellular signalling network is presented. In detail, the parameter sensitivity analysis verifies the good agreement with data of the literatures.Inspec keywords: genetics, differential equations, sensitivity analysis, biology, sampling methods, optimisationOther keywords: biological systems, metabolic networks, genetic circuits, Morris‐based sensitivity calculation, ordinary differential equation, sampling trajectory optimisation, sensitivity analysis, parameter sensitivity analysis, cellular signalling network |
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