Team:NTU Taida/M1

From 2014.igem.org

(Difference between revisions)
Line 25: Line 25:
   </head>
   </head>
   <body>
   <body>
-
     <nav class="navbar navbar-default navbar-fixed-top" role="navigation" style="padding-top:20px">
+
     <nav class="navbar navbar-default navbar-fixed-top" role="navigation" >
   <div class="container-fluid">
   <div class="container-fluid">
     <!-- Brand and toggle get grouped for better mobile display -->
     <!-- Brand and toggle get grouped for better mobile display -->
Line 35: Line 35:
         <span class="icon-bar"></span>
         <span class="icon-bar"></span>
       </button>
       </button>
-
       <a href="https://2014.igem.org/Team:NTU_Taida"><img id="logo" height="50" src="https://static.igem.org/mediawiki/2014/1/19/NTU_Taida_logo.jpg"></a>
+
       <a href="https://2014.igem.org/Team:NTU_Taida"><img id="logo" width="70px" src="https://static.igem.org/mediawiki/2014/1/19/NTU_Taida_logo.jpg"></a>
     </div>
     </div>

Revision as of 00:53, 18 October 2014

NTU-Taida

In theories modeling part, we focus on the interpretation of experimental data and predict the outcomes with different initial conditions, which means the different initial concentration of fatty acid.

Our Simulation Progress

1. Prediction of fundamentals of exfoliation circuit

In our circuit design of exfoliation, one of core concept is using lambda repressor(CI) to regulate the gene expression of keratinase. We have written a script in matlab to simulate this system repression according to [9]. In our simulation, we assume that when pfdba promoter is working, it will work as constitutive promoter,and the mathematical descriptions of the model are:

The model consists of basal expression(α0Y),protein synthesis(αC,αY),repressor binding(βC),protein decay(γC,γY) and repressor cooperativity(ηC) for CI(C) and keratinase(Y).Following figure 1 shows the result of simulation.

Fig 1 simulation prediction of exfoliation circuit
2. Deterministic modeling of whole whitening circuit

To introduce our three mathematical models, we first indicate and compare the difference between each model constructing a more clearly outline.

Model 3 separates the original model using αoc,αc(αoc is the steady state; αc is the maximum transcription rate) to express the linear part and non-linear part of the system. Model 1 isolate the RBS strength, activator and repressor from the original equation. The whole function is the multiplication of RBS strength, activator and repressor. The RBS strength here is equivalent to the maximum transcription rate.