Team:NCTU Formosa/modeling

From 2013.igem.org

(Difference between revisions)
(Plux efficiency)
(Small RNA-regulated System)
Line 47: Line 47:
The data is about P<sub>lux</sub> under different concentration of AHL and different time.</p>
The data is about P<sub>lux</sub> under different concentration of AHL and different time.</p>
[[File:Plux_testbiobrick.jpg|400px|center|Figure.1 the biobrick to test expression of the lux promoter.]]
[[File:Plux_testbiobrick.jpg|400px|center|Figure.1 the biobrick to test expression of the lux promoter.]]
-
[[file:Nctu_Plux_ahl_time_wikifig.jpg|500px|center|Figure.2(undetermined)]]
+
[[File:Nctu_Plux_train_wikifig.jpg|745px|center|Figure.2(undetermined)]]
-
[[File:Nctu_Plux_train_wikifig.jpg|745px|center|Figure.3(undetermined)]]
+
[[file:Nctu_Plux_ahl_time_wikifig.jpg|500px|center|Figure.3(undetermined)]]
 +
 
======Reference======
======Reference======
<div class="rev">
<div class="rev">

Revision as of 03:14, 27 October 2013

Modeling

Modeling was our first step forward. When validated with our experimental data, modeling is also a verification of the accuracy of our experiments.

Change the font size right here

Contents

MATLAB Introduction

MATLAB (matrix laboratory) is a numerical computing environment and fourth-generation programming language. It is developed by MathWorks, a company in United States. MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, Java, and Fortran. Although MATLAB is intended primarily for numerical computing, an optional toolbox uses the MuPAD symbolic engine, allowing access to symbolic computing capabilities. An additional package, Simulink, adds graphical multi-domain simulation and Model-Based Design for dynamic and embedded systems.


Fig.  Images of MATLAB

ANFIS Introduction

Adaptive-Network-Based Fuzzy Inference System, in short ANFIS, is a power tool for constructing a set of fuzzy if-then rules to generate stipulated output and input pairs. Unlike system modeling using mathematical rules that lacks the ability to deal with ill-defined and uncertain system, ANFIS can transform human knowledge into rule base, and therefore, ANFIS can effectively tune membership functions, minimizing the output error.

Light-regulated System

Red Promoter

Temperature-regulated system

Figure 1. Input 1= Time (hr), Input 2= Temperature (oC), Output = Normalized expression (AU).


From Figure 1, the maximum output is obtained at 37oC. Under the same time frame, the output (the normalized expression of the reporter gene) is maximized at 37oC while minimized at 25oC. There is a dramatic decrease in the output near 30o and the outputs around 37oC are much higher. This modeling demonstrates that using 37oC RBS is a plausible approach for achieving gene expression through temperature.

Small RNA-regulated System

Plux efficiency

We searched the biobrick like figure.1 and got the data from Imperial 2007 iGEM team. The data is about Plux under different concentration of AHL and different time.

Figure.1 the biobrick to test expression of the lux promoter.
Figure.2(undetermined)
Figure.3(undetermined)
Reference
  1. iGEM 2007 Imperial https://2007.igem.org/Imperial