## page was renamed from Meetings/C1netWork2/Practicals/Practical 5
## page was renamed from Meetings/C1netWork2/Prac9
== Practical 5: Kinetics of the Calvin Cycle. ==
For this practical we will be investigating the control analysis properties  of the Calvin cycle described in the previous lecture. Download it [[http://mudsharkstatic.brookes.ac.uk/C1Net/Wshop2/Models/calvin1.spy|here]].

The goal is to generate a dataset in which the rows are the Vmax values of the enzymes in the model, and the columns the reactions. Each cell will contain the flux control coefficient  of reaction fluxes to Vmax.

 1. Having loaded the model, we need to create a dataset to hold our results, the item names will be the names of the reactions in the model:
  *
  {{{
>>> fccs = DataSets.DataSet(ItemNames=m.sm.cnames)
}}}


 1. The names of the Vmax parameters are:
  *
  {{{
>>> vms =['FBPase_ch_vm', 'SBPase_ch_vm', 'TP_Piap_vm', 'Ru5Pk_ch_vm', 'LR_vm', 'Rbco_vm', 'StSynth_vm', 'StPase_vm', 'EQMult']
}}}

   *
   This line can be copied and pasted into the !ScrumPy command line.



 1. Now, for each Vmax, we need to calculate the sensitivity of the steady-state reaction rates to a small change in the Vmax value:
  *
  {{{
>>> for v in vms:
        result = m.ScaledSensits(v, m.sm.cnames)
        fccs.NewRow(result, name=v)
}}}


 1.
 The !DataSet, fccs, can be examined from within !ScrumPy, but it may be more convenient to save it as a file and view it using the !LibreOffice spreadsheet:

  *
  {{{
>>> print >>open("fccs.txt","w"), fccs
}}}

  * This saves the results in a file called "fccs.txt". You can load this into !LibreOffice by selecting File/New/Spreadsheet followed by Insert/Sheet from file.  (On import, use space as delimiter, and merge delimiters.)

 1. The matrix of control coefficients contains a great deal of information about the network. Firstly the network contains a number of subsets - identify them from the matrix, and compare them to those obtained from the null-space (or m.!EnzSubsets()).
 1. There are three transport fluxes of interest, assimilation, export (sum of the TPT fluxes) and storage (flux in PGI and/or PGM). How does the control of these three fluxes differ?
 1. The assimilation reaction (Rubisco) is a member of a subset.  Compare the ratio of the steady-state fluxes in these reactions to their respective Vmax values (m["Rubisco"] / m["Rbco_vm"] etc.) to their control coefficients. Suggest a way (by changing Vmax values) to move control of assimilation to other reactions in the same subset.
 1. What effect does this have on the control of export and storage?