Parameter estimation of an S-system model using hybrid genetic algorithm with the aid of sensitivity analysis

9 Jul 2018, 10:50
New Law School/--022 (University of Sydney)

New Law School/--022

University of Sydney

Oral Presentation Techniques for Mathematical Biology Biochemistry, signalling & mathematical techniques


Dr Renier Mendoza (Institute of Mathematics University of the Philippines Diliman)


A biochemical system is a biological system consisting of a collection of chemical compounds interacting with each other. One way to model and analyze a biochemical system is by using S-systems, which are coupled ordinary differential equations based on power-law formalism. In this work, we do a parameter estimation on an S-system model called HS96. This model, proposed by Hlavacek and Savageau in 1996, describes a simple genetic network consisting of five dependent variables $X_i,$ $i=1,2,...,5$. As a preliminary method, sensitivity analysis of HS96 is conducted to investigate the change in model outputs with respect to the changes in model parameters. Usual model outputs are $X_i$ and $\dot{X}_i,$ $i=1,2,...,5$. From the results of sensitivity analysis, model outputs are selected which are then used to estimate the parameters of the HS96 model. A hybrid of genetic algorithm with the interior point method is used in the parameter estimation.

Primary author

Dr Renier Mendoza (Institute of Mathematics University of the Philippines Diliman)


Ms Jayrah Bena Riñon (Institute of Mathematics, University of the Philippines, Diliman) Dr Victoria May Paguio (Institute of Mathematics, University of the Philippines Diliman)

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