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Alan Weiss
on 6 Sep 2021

Add the parameters to optimize as a vector in your ODE calculation:

function rest = Scrpt1(t,X,params)

x2 = X(1);

x3 = X(2);

%Parameters

if t<15

x1 = params(1); %Input 1 could vary from 1e-9 to 1e-6

else

x1 = 0;

end

x5 = params(2); %Input 2 (Input 2 is a state variable and could vary in range of 4 to 15 while performing optimization)

kst = params(3); %Input 3 (Input 3 is in terms of rate constant, it could vary from 0.1 to 2)

xo = params(4); %Input 4 (Input 4 is a state variable and could vary in range of 4 to 10)

k1 = 6e7;

km1 = 0.20;

km4 = 0.003;

k3 = 2500.00;

k4 = km4/9;

km3 = km1;

LAP = 1.5;

%Differential equations

dx2dt = km1*x3 + km3*LAP - k1*x1*x2 + km4*x3 - k4*x2;

dx3dt = k1*x1*x2 - km1*(x3+x5+xo) - k3*x3*kst;

rest = [dx2dt; dx3dt];

end

Write your objective function as follows:

function y = objfun(params)

options = odeset('InitialStep',0.0001,'RelTol',1e-09);

[~,Y] = ode15s(@(t,X)Scrpt1(t,X,params),[0 60],[9e-13,0],options);

y = -Y(end,2); % Negative because you want to maximize

% I assume that you want the value of Y at the last time

end

Obtain the solution:

lb = [1e-9,4,0.1,4];

ub = [1e-6,15,2,10];

x0 = [1e-7,5,1,4];

opts = optimoptions("fmincon","PlotFcn","optimplotfval");

[sol,fval] = fmincon(@objfun,x0,[],[],[],[],lb,ub,[],opts)

% The true function value is -fval because you negated y

Alan Weiss

MATLAB mathematical toolbox documentation

Alan Weiss
on 8 Aug 2021

I don't know what an SBML file is. But to optimize an ODE you can look at these examples:

Alan Weiss

MATLAB mathematical toolbox documentation

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