User:James Chappell /R RK4 Modeling: Difference between revisions
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'''Example 1 : Simple Constitutive Expression''' | '''Example 1 : Simple Constitutive Expression''' | ||
constitutiveexpression <- function(t, x, parms) { | (constitutiveexpression <- function(t, x, parms) { | ||
Define the name of the model | #Define the name of the model | ||
mRNA <- x[1] | mRNA <- x[1] | ||
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protein <- x[2] | protein <- x[2] | ||
Name the response variables – these are the outputs of our model | #Name the response variables – these are the outputs of our model | ||
with(as.list(parms),{ | with(as.list(parms),{ | ||
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})} | })} | ||
Combine these vectors into a list called res | #Combine these vectors into a list called res | ||
times <-seq(0, 1000, length=1001) | times <-seq(0, 1000, length=1001) | ||
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parms <-c(k1=0.69 , k2=f ,d1=0.23 ,d2=0.012) | parms <-c(k1=0.69 , k2=f ,d1=0.23 ,d2=0.012) | ||
Generate a time series over which to solve the equations (1000 in steps of 1) | #Generate a time series over which to solve the equations (1000 in steps of 1) | ||
Set the parameter values in parms | #Set the parameter values in parms | ||
y <- xstart <-c (mRNA=1, protein=1) | y <- xstart <-c (mRNA=1, protein=1) | ||
Set the starting value for response variables | #Set the starting value for response variables | ||
output <- as.data.frame(rk4(xstart, times, constitutiveexpression, parms)) | output <- as.data.frame(rk4(xstart, times, constitutiveexpression, parms)) | ||
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plot(output$time, output$protein, ylim=c(0,2000), ylab="protein (molecules)",xlab="time (min)",type="n") | plot(output$time, output$protein, ylim=c(0,2000), ylab="protein (molecules)",xlab="time (min)",type="n") | ||
} | } | ||
</div> | </div> | ||
Revision as of 08:19, 8 July 2009
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James Chappell
Imperial College London Synthetic Biology Lab
RK4
The RK4 tool is a tool that can be used to model ordinary differential equations (ODE). Like other ODE solvers you can output the results of a simulation into graph or tables.
Example 1 : Simple Constitutive Expression
(constitutiveexpression <- function(t, x, parms) {
- Define the name of the model
mRNA <- x[1]
protein <- x[2]
- Name the response variables – these are the outputs of our model
with(as.list(parms),{
dmRNA <- k1 - d1*mRNA
dprotein <- k2*mRNA - d2*protein
res<-c(dmRNA, dprotein)
list(res)
})}
- Combine these vectors into a list called res
times <-seq(0, 1000, length=1001)
parms <-c(k1=0.69 , k2=f ,d1=0.23 ,d2=0.012)
- Generate a time series over which to solve the equations (1000 in steps of 1)
- Set the parameter values in parms
y <- xstart <-c (mRNA=1, protein=1)
- Set the starting value for response variables
output <- as.data.frame(rk4(xstart, times, constitutiveexpression, parms))
plot(output$time, output$protein, ylim=c(0,2000), ylab="protein (molecules)",xlab="time (min)",type="n") }
