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- | [[Image:f7DCA.png|thumb]] At the steady-state, we have
| + | {{Paris/Menu}} |
| | | |
- | <center>[[Image:FlhDCeq.jpg]]</center> | + | {{Paris/Header|Method & Algorithm : ƒ7}} |
- | and
| + | <center> = act_''pTet'' </center> |
- | <center>[[Image:FliAeq.jpg]]</center> | + | <br> |
| | | |
- | so the expression
| + | [[Image:f7DCA.png|thumb|Specific Plasmid Characterisation for ƒ7]] |
| | | |
- | <center>[[Image:f7expr.jpg]]</center>
| + | According to the characterization plasmid (see right) and to our modeling, in the '''exponential phase of growth''', at the steady state, |
| | | |
- | gives
| + | we have ''' [''FlhDC'']<sub>''real''</sub> = {coef<sub>''flhDC''</sub>} ƒ1([aTc]<sub>i</sub>) ''' |
| + | and ''' [''FliA'']<sub>''real''</sub> = {coef<sub>''fliA''</sub>} ƒ2([arab]<sub>i</sub>) ''' |
| | | |
- | <center>[[Image:f7FlhDC.jpg]]</center>
| + | but we use ''' [aTc]<sub>i</sub> = Inv_ƒ1( [''FlhDC''] ) ''' |
- | and | + | and ''' [arab]<sub>i</sub> = Inv_ƒ2( [''FliA''] ) ''' |
- | <center>[[Image:f7FliA.jpg]]</center>
| + | |
| | | |
- | and for ''calculated values of the TF'',
| + | So, at steady-states, |
| | | |
- | <center>[[Image:f7FlhDCCalc.jpg]]</center>
| + | [[Image:F7a.jpg|center]] |
- | and
| + | |
- | <center>[[Image:f7FliACalc.jpg]]</center>
| + | |
| | | |
- | <br><br>
| + | we use this analytical expression to determine the parameters : |
| | | |
- | {|border="1" style="text-align: center"
| + | <div style="text-align: center"> |
- | |param | + | {{Paris/Toggle|Table of Values|Team:Paris/Modeling/More_f7_Table}} |
- | |signification
| + | </div> |
- | |unit
| + | |
- | |value
| + | |
- | |-
| + | |
- | |[expr(pFlgB)]
| + | |
- | |expression rate of <br> pFlgB '''with RBS E0032'''
| + | |
- | |nM.min<sup>-1</sup>
| + | |
- | |see [[Team:Paris/Modeling/Programs|"findparam"]] <br> need for 20 + 20 measures <br> and 5x5 measures for the ''SUM''? | + | |
- | |-
| + | |
- | |γ<sub>GFP</sub>
| + | |
- | |dilution-degradation rate <br> of GFP(mut3b)
| + | |
- | |s<sup>-1</sup>
| + | |
- | |0.0198
| + | |
- | |-
| + | |
- | |[GFP]
| + | |
- | |GFP concentration at steady-state
| + | |
- | |nM
| + | |
- | |need for 20 + 20 measures <br> and 5x5 measures for the ''SUM''?
| + | |
- | |-
| + | |
- | |(''fluorescence'')
| + | |
- | |value of the observed fluorescence
| + | |
- | |au
| + | |
- | |need for 20 + 20 measures <br> and 5x5 measures for the ''SUM''?
| + | |
- | |-
| + | |
- | |''conversion''
| + | |
- | |conversion ration between <br> fluorescence and concentration
| + | |
- | |nM.au<sup>-1</sup>
| + | |
- | |(1/79.429)
| + | |
- | |}
| + | |
| | | |
- | <br><br> | + | <div style="text-align: center"> |
| + | {{Paris/Toggle|Algorithm|Team:Paris/Modeling/More_FP_Algo}} |
| + | </div> |
| | | |
- | {|border="1" style="text-align: center"
| + | Then, if we have time, we want to verify the expected relation |
- | |param
| + | |
- | |signification <br> corresponding parameters in the [[Team:Paris/Modeling/Oscillations#Resulting_Equations|equations]]
| + | |
- | |unit
| + | |
- | |value
| + | |
- | |-
| + | |
- | |β<sub>57</sub>
| + | |
- | |production rate of FlhDC-pFlgB '''with RBS E0032''' <br> β<sub>57</sub>
| + | |
- | |nM.min<sup>-1</sup>
| + | |
- | |
| + | |
- | |-
| + | |
- | |(K<sub>51</sub>/{coef<sub>flhDC</sub>})
| + | |
- | |activation constant of FlhDC-pFlgB <br> K<sub>51</sub>
| + | |
- | |nM
| + | |
- | |
| + | |
- | |-
| + | |
- | |n<sub>51</sub>
| + | |
- | |complexation order of FlhDC-pFlgB <br> n<sub>51</sub>
| + | |
- | |no dimension
| + | |
- | |
| + | |
- | |-
| + | |
- | |-
| + | |
- | |β<sub>58</sub>
| + | |
- | |production rate of FliA-pFlgB '''with RBS E0032''' <br> β<sub>52</sub>
| + | |
- | |nM.s<sup>-1</sup>
| + | |
- | |
| + | |
- | |-
| + | |
- | |(K<sub>52</sub>/{coef<sub>fliA</sub>})
| + | |
- | |activation constant of FliA-pFlgB <br> K<sub>52</sub>
| + | |
- | |nM
| + | |
- | |
| + | |
- | |-
| + | |
- | |n<sub>52</sub>
| + | |
- | |complexation order of FliA-pFlgB <br> n<sub>52</sub>
| + | |
- | |no dimension
| + | |
- | |
| + | |
- | |}
| + | |
| | | |
- | <br><br>
| + | [[Image:SumpFlgB.jpg|center]] |
| | | |
- | Then, if we have time, we want to verify the expected relation
| + | <br> |
| | | |
- | <center>[[Image:SumpFlgB.jpg]]</center> | + | <center> |
| + | [[Team:Paris/Modeling/Implementation| <Back - to "Implementation" ]]| <br> |
| + | [[Team:Paris/Modeling/Protocol_Of_Characterization| <Back - to "Protocol Of Characterization" ]]| |
| + | </center> |
Method & Algorithm : 7
= act_pTet
Specific Plasmid Characterisation for 7
According to the characterization plasmid (see right) and to our modeling, in the exponential phase of growth, at the steady state,
we have [FlhDC]real = {coefflhDC} 1([aTc]i)
and [FliA]real = {coeffliA} 2([arab]i)
but we use [aTc]i = Inv_1( [FlhDC] )
and [arab]i = Inv_2( [FliA] )
So, at steady-states,
we use this analytical expression to determine the parameters :
↓ Table of Values ↑
param
| signification
| unit
| value
| comments
|
(fluorescence)
| value of the observed fluorescence
| au
|
| need for 20 mesures with well choosen values of [aTc]i and for 20 mesures with well choosen values of [arab]i and 5x5 measures for the relation below?
|
conversion
| conversion ratio between fluorescence and concentration ↓ gives ↓
| nM.au-1
| (1/79.429)
|
|
[GFP]
| GFP concentration at steady-state
| nM
|
|
|
γGFP
| dilution-degradation rate of GFP(mut3b) ↓ gives ↓
| min-1
| 0.0198
| Time Cell Division : 35 min.
|
7
| activity of pFlgB with RBS E0032
| nM.min-1
|
|
|
param
| signification corresponding parameters in the equations
| unit
| value
| comments
|
β28
| total transcription rate of FlhDC><pFlgB with RBS E0032 β28
| nM.min-1
|
|
|
(K4/{coeffliA})
| activation constant of FlhDC><pFlgB K4
| nM
|
|
|
n4
| complexation order of FlhDC><pFlgB n4
| no dimension
|
|
|
β29
| total transcription rate of FlhDC><pFlgB with RBS E0032 β29
| nM.min-1
|
|
|
(K10/{coefflhDC})
| activation constant of FlhDC><pFlgB K10
| nM
|
|
|
n10
| complexation order of FlhDC><pFlgB n10
| no dimension
|
|
|
|
↓ Algorithm ↑
find_P
function optimal_parameters = find_FP(X_data, Y_data, initial_parameters)
function output = act_pProm(parameters, X_data)
for k = 1:length(X_data)
output(k) = parameters(1)*hill(X_data(k), parameters(2), parameters(3));
end
end
options=optimset('LevenbergMarquardt','on','TolX',1e-10,'MaxFunEvals',1e10,'TolFun',1e-10,'MaxIter',1e4);
optimal_parameters = lsqcurvefit( @(parameters, X_data) act_pProm(parameters, X_data),...
initial_parameters, X_data, Y_data, options );
end
|
Then, if we have time, we want to verify the expected relation
<Back - to "Implementation" |
<Back - to "Protocol Of Characterization" |
|