Team:Colombia Uniandes/Scripting
From 2013.igem.org
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Revision as of 22:19, 25 September 2013
Scripting
Contents |
Glucocorticoid Detection System
Deterministic model
Equations
function y = EcuacionesGluco(t,x) global gammaGR mGRIR mCC deltaGRI alfaR deltaR deltaCC betaCC k n deltaS H % %---------Parameters------% % % GRO=funcImpulso(t); % %------ Variables%------% % GRI= x(1); %Glucocorticoid inside the cell R=x(2); %Receptor in the cytoplasm CC=x(3); %Receptor -Glucocorticoid complex V=x(4); %Violacein % % %---Equations---% dGRI=gammaGR*(GRO-GRI)-mGRIR*GRI*R+mCC*CC-deltaGRI*GRI; dR=alfaR-mGRIR*GRI*R+mCC*CC-deltaR*R; dCC=mGRIR*GRI*R-mCC*CC-deltaCC*CC-(betaCC*CC.^n)/(k^n+CC.^n);%Revisar dV=H*(betaCC*CC^n)/(k^n+CC^n)-deltaS*V; % y1(1)=dGRI; y1(2)=dR; y1(3)=dCC; y1(4)=dV; % % y= y1'; % end
Equation solver
%global gammaGR mGRIR mCC deltaGRI alfaR deltaR deltaCC betaCC k n deltaS H % % gammaGR= 0.1; %Diffussion rate of glucocorticoid inside the cell (mm/min) % mGRIR=1.080e-3; % GRI-R complex formation kinetic constant (1/umol min) % mCC=1.14*10^-8; %GRI-R Complex formation reverse kinetic constant (1/min) % deltaGRI=0.00833; %Glucocorticoids Destruction rate inside the cell (1/min) % alfaR= 0.8e3; %Basal production rate of the receptor (umol/min) % deltaR=0.004166; %Receptor destruction rate inside the cell (1/min) deltaCC=0.004166; % GRI-R complex Destruction rate (1/min) betaCC=0.5e3; % GRI-R complex maximum expression rate (umol/min) k=0.05e3; %Hill's constant for the GRI-R complex dimmer binding to his respective region (umol) n=2; %Hill coefficient (cooperation constant) deltaS=0.04166; %Signal destruction rate (1/min) H=2; %Correction constant for the signal % % % h=60; %Tiempo maximo % m=0.01; %Longitud de paso [s] % t=0:m:h; %Vector tiempo % xi=[0 0 0 0]; % y=fsolve(@CondIndGluco,xi,optimset('algorithm','levenberg-marquardt','maxiter',100000,'tolfun',1e-9)); % conInd=y; assignin('base','conInd',conInd); l=(0:m:h)'; %Vector de tiempo % x=zeros(length(l),length(conInd)); %Matriz de variables, en las columnas varia %la variable y en las filas varia el tiempo % GRO=zeros(1,length(l)); % x(1,:)=conInd; % for u=1:length(l)-1 % xk=x(u,:); %Captura de la ultima posicion de la matirz, es decir, los %valores actuales de las variables % k1=EcuacionesGluco(l(u),xk); %Primera pendiente del metodo de RK4 k2=EcuacionesGluco(l(u)+m/2,xk+(m/2*k1)'); %Segunda pendiente del metodo de RK4 k3=EcuacionesGluco(l(u)+m/2,xk+(m/2*k2)'); %Tercera pendiente del metodo de RK4 k4=EcuacionesGluco(l(u)+m,xk+(m*k3)'); %Cuarta pendiente del metodo de RK4 % xk1=xk+m/6*(k1+2*k2+2*k3+k4)'; %Calculo de nuevos valores para las %variables % % xk2=zeros(1,length(xk1)); % % for p=1:length(xk1) % if(xk1(p)<0.00000001) % xk2(p)=0; else % xk2(p)=xk1(p); end % end % % x(u+1,:)=xk2; %Actualizacion del nuevo vector de variables en la matriz % % % % % end % for j=1:length(l) % if (l(j)<(10) || l(j)>(30)) % GRO(j)=155; % else % GRO(j)=155*1.3; % % end % % end % GRI=x(:,1); R=x(:,2); CC=x(:,3); V=x(:,4); % % figure(1) plot(l,R)%,l,GRO)%,l,CC,l,V) legend('Receptor')%,'Glucocorticoid') %, 'Complex', 'Signal') xlabel('Time') ylabel('Concetration (micromolar)') title('Glucocorticoid model') % figure(2) plot(l,CC)%,l,GRO) legend('Complejo')%,'Glucocorticoid') % figure(3) plot(l,V)%,l,GRO) legend('Senal')%,'Glucocorticoid') % figure(4) plot(l,GRI)%,l,GRO) legend('GRI')%,'Glucocorticoid') %
Stochastic
Nickel removal system
Deterministic model
Equations
function y = EqNick(x,t)
%--Parameters---%
global gammaN Kp beta Kd Kx alfaR deltaR Kt deltaT n alfaP deltaP
No=x(1); % Niquel outside the cell
%------ Variables%------%
Ni= x(2); %Nickel Inside the cell R=x(3); %RcnR (Repressor) T=x(4); %RcnR Tetramer P=x(5); %Porine
%---Equations---%
dNo=-gammaN*(No-Ni) - Kp*P*No; dNi=gammaN*(No-Ni) + Kp*P*No- beta/(1 + (T/(Kd*(1+(Ni/Kx))^n))); dR=alfaR-deltaR*R - Kt*R^4; dT= Kt*R^4 - deltaT*T - beta/(1 + (T/(Kd*(1+(Ni/Kx))^n))); dP=alfaP - deltaP*P + beta/(1 + (T/(Kd*(1+(Ni/Kx))^n)));
y1(1)=dNo; y1(2)=dNi; y1(3)=dR; y1(4)=dT; y1(5)=dP;
y= y1';
end
Equation solver
clear all clc
%---------Parameters------%
global gammaN Kp beta Kd Kx alfaR deltaR Kt deltaT n alfaP deltaP
gammaN=0.5034e-4; %Diffussion rate of Nickel (1/min) Kp=0.000634; %Dynamic constant for the entrance of nickel to the cell beta=0.166; %Porine maximum expression rate (nM/min) Kd=276e-3; %Association constant DNA and repressor (nM) Kx=25e-3; %Association constant of the repressor with nickel (nM) alfaR= 5; %Represor basal production rate (nM/min) deltaR=1/1200; % Represor destruction rate (1/min) Kt=820e-3;% Rate constant for the formation of the tetramer (Giraldo et al) deltaT=1/1200; %Tetramer destruction rate (!/min) n=1; %Hill coefficient (cooperation constant) alfaP=0.031; %Porine basal production rate (nM/min) deltaP=1/1200;%Porine destruction rate (1/min)
yo=[0 0 0 0];
con=fsolve(@(x)CondIniciales(x),yo, optimset('display','iter','MaxIter',1000000,'algorithm','levenberg-marquardt','tolfun',1e-9));
assignin('base','ini',con);
cond=abs(con);
h=30; %Tiempo maximo m=0.01; %Paso l=(0:m:h);%Vector de tiemp
condI=[9.88e3 cond]; x=zeros(length(l),length(condI)); x(1,:)=condI;
for k=1:length(l)-1
xk=x(k,:); %Captura de la ultima posicion de la matirz, es decir, los %valores actuales de las variables k1=EqNick(xk,l(k)); %Primera pendiente del metodo de RK4 k2=EqNick(xk+(m/2*k1)',l(k)+m/2); %Segunda pendiente del metodo de RK4 k3=EqNick(xk+(m/2*k2)',l(k)+m/2); %Tercera pendiente del metodo de RK4 k4=EqNick(xk+(m*k3)',l(k)+m); %Cuarta pendiente del metodo de RK4 xk1=xk+m/6*(k1+2*k2+2*k3+k4)'; %Calculo de nuevos valores para las %variables %xk1=xk+m*ecuaDif(l(k),xk)'; %Method of Newton xk2=zeros(1,length(xk1)); for p=1:length(xk1) if(xk1(p)<0.00000001) xk2(p)=0; else xk2(p)=xk1(p); end end x(k+1,:)=xk2; %Actualizacion del nuevo vector de variables en la matriz
end
No=x(:,1); Ni=x(:,2); assignin('base','No',No); assignin('base','Nistable',Ni(length(Ni))); disp(Ni(length(Ni))) R=x(:,3); assignin('base','Rstable',R(length(R))); T=x(:,4); assignin('base','Tstable',T(length(T))); P=x(:,5); assignin('base','Pstable',P(length(P))); cond=[R(length(R)) T(length(T)) P(length(P))]; assignin('base','cond',cond); figure(1) plot(l,No,l,P) legend('No','P') xlabel('Time (min)') ylabel('Concentration (nM)') figure(2) plot(l,Ni) legend('Ni') xlabel('Time (min)') ylabel('Concentration (nM)') figure(3) plot(l,R) legend('R') xlabel('Time (min)') ylabel('Concentration (nM)') figure(4) plot(l,T) legend('T') xlabel('Time (min)') ylabel('Concentration (nM)') figure(5) plot(l,P) legend('P') xlabel('Time (min)') ylabel('Concentration (nM)')