dev/fittingNoisyResultsScrap.R

In ffeng23/ADASPR: An R package to characterize the distributed affinities in a multi-ligand system

for 2000 dissociationLength

dissociationLength<-2000  #3000
Rmax<-c(80, 80, 70)


mlgm<- new("MultiLigandModel", kon=kon, koff=koff, analyteConcentrations=analyteConcentrations, 
           associationLength=associationLength, dissociationLength=dissociationLength, Rmax=Rmax)
set.seed(2)		
sData<-Simulate(mlgm,sampleFreq=0.01, sd=0.1)	 #for kon us sampleFreq=0.05
plot(sData[[1]])
fss<-FitSteadyStateSPR(sData[[1]], degree=5, steadyStateStart=2950,steadyStateEnd=3000, auto=T)

fcp.on<-fitSPR.kon(sData[[1]],debug=TRUE,weights.type="exp", weights.step=1.0, weights.scale=71.5
			)#step 10~20, weights.scale=8.5


e_k<-rep(0,length(analyteConcentrations))
e_k[1]<-sum(koff/kon*(Rmax/sum(Rmax)))
e_k[2]<-sum((koff/kon)^2*(Rmax/sum(Rmax)))
e_k[3]<-sum((koff/kon)^3*(Rmax/sum(Rmax)))
e_k[4]<-sum((koff/kon)^4*(Rmax/sum(Rmax)))

#first get the distribution of Rmax
E_kon<-rep(0,length(kon))
E_kon[1]<-sum(Rmax/sum(Rmax)*kon)
E_kon[2]<-sum(Rmax/sum(Rmax)*kon^2)
E_kon[3]<-sum(Rmax/sum(Rmax)*kon^3)
E_kon[4]<-sum(Rmax/sum(Rmax)*kon^4)
E_kon[5]<-sum(Rmax/sum(Rmax)*kon^5)

fpc.off<-fitSPR.koff(sData[[1]], debug=TRUE,degree.fitMoments=3,  weightsType.fitSPR="exp",degree.fitSPR=6,#7
			,weightsScale.fitSPR=150, weightsStep.fitSPR=0.01, 
			weightsType.fitMoments="exp", weightsScale.fitMoments=0.5);
			
			
			
			
~~~~~~~~~~~~~~~~~~~~~~
> associationLength<-3000
> dissociationLength<-3000
> Rmax<-c(80, 80, 70)
> 
> 
> mlgm<- new("MultiLigandModel", kon=kon, koff=koff, analyteConcentrations=analyteConcentrations, 
+            associationLength=associationLength, dissociationLength=dissociationLength, Rmax=Rmax)
> set.seed(2)
> sData<-Simulate(mlgm,sampleFreq=0.01, sd=0.1) #for kon us sampleFreq=0.05
> plot(sData[[1]])
> fss<-FitSteadyStateSPR(sData[[1]], degree=5, steadyStateStart=2950,steadyStateEnd=3000, auto=T)
Waiting to confirm page change...
Waiting to confirm page change...
> 
> fcp.on<-fitSPR.kon(sData[[1]],debug=TRUE,weights.type="exp", weights.step=1.0, weights.scale=71.5
+ )#step 10~20, weights.scale=8.5
doing fitting the SPR sensorgrams......
doing fitting for moments of kon.......5  debugging plots written to  C:/Users/Temp/Documents 
fitting information has been written to file at
         C:/Users/Temp/Documents debug.txt
> 
> 
> e_k<-rep(0,length(analyteConcentrations))
> e_k[1]<-sum(koff/kon*(Rmax/sum(Rmax)))
> e_k[2]<-sum((koff/kon)^2*(Rmax/sum(Rmax)))
> e_k[3]<-sum((koff/kon)^3*(Rmax/sum(Rmax)))
> e_k[4]<-sum((koff/kon)^4*(Rmax/sum(Rmax)))
> 
> #first get the distribution of Rmax
> E_kon<-rep(0,length(kon))
> E_kon[1]<-sum(Rmax/sum(Rmax)*kon)
> E_kon[2]<-sum(Rmax/sum(Rmax)*kon^2)
> E_kon[3]<-sum(Rmax/sum(Rmax)*kon^3)
> E_kon[4]<-sum(Rmax/sum(Rmax)*kon^4)
> E_kon[5]<-sum(Rmax/sum(Rmax)*kon^5)
> 
> fpc.off<-fitSPR.koff(sData[[1]], debug=TRUE,degree.fitMoments=3,  weightsType.fitSPR="exp",degree.fitSPR=7,
+ ,weightsScale.fitSPR=220, weightsStep.fitSPR=0.05, 
+ weightsType.fitMoments="exp", weightsScale.fitMoments=0.5);
doing fitting the SPR sensorgrams......
doing fitting for moments of koff.......3  debugging plots written to  C:/Users/Temp/Documents 
fitting information has been written to file at
         C:/Users/Temp/Documents debug.txt
> 
> for(i in 1:length(analyteConcentrations))
+ {
+ E_koff1[i]<-sum(koff*r0[i,]/sum(r0[i,]))
+ E_koff2[i]<-sum(koff^2*r0[i,]/sum(r0[i,]))
+ E_koff3[i]<-sum(koff^3*r0[i,]/sum(r0[i,]))
+ E_koff4[i]<-sum(koff^4*r0[i,]/sum(r0[i,]))
+ 
+ }
Error: object 'r0' not found
> 
> 
> #expected koff moments over Rmax
> E_koff<-rep(0,7)
> E_koff[1]<-sum(Rmax)
> E_koff[2]<-sum(koff*Rmax/sum(Rmax))
> E_koff[3]<-sum(koff^2*Rmax/sum(Rmax))
> E_koff[4]<-sum(koff^3*Rmax/sum(Rmax))
> E_koff[5]<-sum(koff^4*Rmax/sum(Rmax))
> E_koff[6]<-sum(koff^5*Rmax/sum(Rmax))
> E_koff[7]<-sum(koff^6*Rmax/sum(Rmax))
> 
> fpc.off[[2]]/230
        Rmax     moment 1     moment 2     moment 3     moment 4     moment 5     moment 6 
1.000056e+00 4.127677e-04 3.527481e-07 3.417701e-10 3.323982e-13 3.344352e-16 3.406694e-19 
> E_koff
[1] 2.300000e+02 4.130435e-04 3.543478e-07 3.484783e-10 3.478913e-13 3.478326e-16
[7] 3.478267e-19
> 
~~~~~~~~~
> set.seed(2)
> sData<-Simulate(mlgm,sampleFreq=0.001, sd=0.1) #for kon us sampleFreq=0.05
> plot(sData[[1]])
> 
> 
> 
> 
> 
> associationLength<-3000
> dissociationLength<-3  #3000
> Rmax<-c(80, 80, 70)
> 
> 
> mlgm<- new("MultiLigandModel", kon=kon, koff=koff, analyteConcentrations=analyteConcentrations, 
+            associationLength=associationLength, dissociationLength=dissociationLength, Rmax=Rmax)
> set.seed(2)
> sData<-Simulate(mlgm,sampleFreq=0.001, sd=0.1) #for kon us sampleFreq=0.05
> plot(sData[[1]])
> 
> 
> 
> 
> 
> 
> 
> 
> 
> fcp.on<-fitSPR.kon(sData[[1]],debug=TRUE,weights.type="exp", degree=10, weights.step=0.05, weights.scale=25
+ )#step 10~20, weights.scale=8.5
doing fitting the SPR sensorgrams......
doing fitting for moments of kon.......5  debugging plots written to  C:/Users/Temp/Documents 
fitting information has been written to file at
         C:/Users/Temp/Documents debug.txt
> 
> fcp.on/230
    moment 1     moment 2     moment 3     moment 4     moment 5 
2.042820e+04 4.776958e+08 1.161737e+13 3.608085e+17 4.457832e+21 
> E_kon
[1] 2.043478e+04 4.826087e+08 1.247826e+13 3.404348e+17 9.595652e+21