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SUMMARY:Parameter estimation of an S-system model using hybrid genetic alg
orithm with the aid of sensitivity analysis
DTSTART;VALUE=DATE-TIME:20180709T005000Z
DTEND;VALUE=DATE-TIME:20180709T011000Z
DTSTAMP;VALUE=DATE-TIME:20230927T081415Z
UID:indico-contribution-312@conferences.maths.unsw.edu.au
DESCRIPTION:Speakers: Renier Mendoza (Institute of Mathematics University
of the Philippines Diliman)\nA biochemical system is a biological system c
onsisting of a collection of chemical compounds interacting with each othe
r. One way to model and analyze a biochemical system is by using S-systems
\, which are coupled ordinary differential equations based on power-law fo
rmalism. In this work\, we do a parameter estimation on an S-system model
called HS96. This model\, proposed by Hlavacek and Savageau in 1996\, desc
ribes a simple genetic network consisting of five dependent variables $X_i
\,$ $i=1\,2\,...\,5$. As a preliminary method\, sensitivity analysis of HS
96 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\, mode
l outputs are selected which are then used to estimate the parameters of t
he HS96 model. A hybrid of genetic algorithm with the interior point metho
d is used in the parameter estimation.\n\nhttps://conferences.maths.unsw.e
du.au/event/2/contributions/312/
LOCATION:University of Sydney New Law School/--022
URL:https://conferences.maths.unsw.edu.au/event/2/contributions/312/
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