Team:Paris/Transduction modeling Deterministic and Stochastic Simulations

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== Modeling ==
 
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* [[Team:Paris/Transduction_modeling#Overview | Introduction]]
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* [[Team:Paris/Transduction_modeling_The Fec Operon as used in our system : chemical equations and kinetics#Overview |A. The Fec Operon as used in our system : chemical equations and kinetics ]]
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* [[Team:Paris/Transduction_modeling_Deterministic and Stochastic Simulations#Overview |B. Deterministic and Stochastic Simulations]]
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==Deterministic and Stochastic Simulations==
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* [[Team:Paris/Transduction_modeling_Results and discussion#Overview |C. Results and discussion]]
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<a class="menu_sub"href="https://2009.igem.org/Team:Paris/DryLab#bottom"> Main </a>|
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<a class="menu_sub"href="https://2009.igem.org/Team:Paris/Production_modeling#bottom"> Delay model</a>|
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<a class="menu_sub"href="https://2009.igem.org/Team:Paris/Production_modeling2#bottom"> Vesicle model</a>|
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<a class="menu_sub_active"href="https://2009.igem.org/Team:Paris/Transduction_modeling#bottom"> Fec simulation</a>
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<a class="menu_sub"href="https://2009.igem.org/Team:Paris/Transduction_modeling#bottom"> Introduction </a>|
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<a class="menu_sub"href="https://2009.igem.org/Team:Paris/Transduction_modeling_The Fec Operon as used in our system : chemical equations and kinetics#bottom"> Fec Operon</a>|
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<a class="menu_sub_active"href="https://2009.igem.org/Team:Paris/Transduction_modeling_Deterministic and Stochastic Simulations#bottom"> Deterministic and stochastic simulations</a>|
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<a class="menu_sub"href="https://2009.igem.org/Team:Paris/Transduction_modeling_Results and discussion#bottom"> Results and conclusion</a>
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==Deterministic and Stochastic Simulations==
 
To study our model, we decided to run two type of simulations.
To study our model, we decided to run two type of simulations.
First of all, we have started with deterministic simulation in order to see whether our description of the chemical cascade reflected our understanding and expected behaviour of the reception system.  
First of all, we have started with deterministic simulation in order to see whether our description of the chemical cascade reflected our understanding and expected behaviour of the reception system.  
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Then, to check whether our system was sensible to molecular noise, we decided to run exact stochastic simulations based on the Gillespie method.
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Then, to check whether our system was sensitive to molecular noise, we decided to run exact stochastic simulations based on the Gillespie method.
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The whole model was built on the Simbiology toolbox of Matlab ; chemical equations as presented [https://2009.igem.org/Team:Paris/Transduction_modeling_The_Fec_Operon_as_used_in_our_system_:_chemical_equations_and_kinetics#Overview here] were written and a the resulting diagram of interaction between species was ploted :
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===Deterministic Model===
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[[Image:Schéma sim bio.tiff|500px|center]]
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ff
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Simulations were performed either in the case of complexation between FecA and FecR or with no complexation between the two species. In each case, different calues for parameter kf_2 were chosen.
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===Deterministic Model===
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We used classical algorithms to solve the system of differential equations and get deterministic simulations ; in each case, according to Cauchy Lipschitz, there exist AN UNIQUE solution for a given set of initial conditions. The results of the deterministic simulation are all gathered here :
===Stochastic Simulations===
===Stochastic Simulations===
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Several runs of stochastic simulations were run for the different values of k and the different initial amounts of FecA. We used a Gillespie algorithm to compute the amounts of molecules at each step  ; the simulations were run with Matlab Simbiology toolbox.
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Below, two graphes issued from our simuations : in the first one, the signal is transducted correctly and the receptor is activated while in the second one, the initial amount of FecA is unable to activate the positive retro action loop.
[[Image:Stochastic.png|600px|center]]
[[Image:Stochastic.png|600px|center]]
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|width=50%| No Complex Formation
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|width=50%| Complex Formation
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{{Template:Paris2009_guided|Transduction_modeling_The_Fec_Operon_as_used_in_our_system_:_chemical_equations_and_kinetics#bottom|Transduction_modeling_Results_and_discussion#bottom}}

Latest revision as of 20:39, 21 October 2009

iGEM > Paris > Reception > Modeling




Deterministic and Stochastic Simulations


To study our model, we decided to run two type of simulations. First of all, we have started with deterministic simulation in order to see whether our description of the chemical cascade reflected our understanding and expected behaviour of the reception system. Then, to check whether our system was sensitive to molecular noise, we decided to run exact stochastic simulations based on the Gillespie method.


The whole model was built on the Simbiology toolbox of Matlab ; chemical equations as presented here were written and a the resulting diagram of interaction between species was ploted :

Schéma sim bio.tiff


Simulations were performed either in the case of complexation between FecA and FecR or with no complexation between the two species. In each case, different calues for parameter kf_2 were chosen.


Deterministic Model

We used classical algorithms to solve the system of differential equations and get deterministic simulations ; in each case, according to Cauchy Lipschitz, there exist AN UNIQUE solution for a given set of initial conditions. The results of the deterministic simulation are all gathered here :

Stochastic Simulations

Several runs of stochastic simulations were run for the different values of k and the different initial amounts of FecA. We used a Gillespie algorithm to compute the amounts of molecules at each step  ; the simulations were run with Matlab Simbiology toolbox.

Below, two graphes issued from our simuations : in the first one, the signal is transducted correctly and the receptor is activated while in the second one, the initial amount of FecA is unable to activate the positive retro action loop.

Stochastic.png


Stochstic inactivation.jpg




Open book.gif

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