Team:ETH Zurich/Modeling/Overview

From 2008.igem.org

(Difference between revisions)
Line 33: Line 33:
* Is it possible to identify a restriction enzyme that optimize the probability reduced but vital strains?
* Is it possible to identify a restriction enzyme that optimize the probability reduced but vital strains?
'''Method:'''<br>
'''Method:'''<br>
-
'''Results:'''<br>
+
E.Coli K12 genome and annotation was digested using 713 different restriction enzymes and statistical analysis applied on the fragment pattern.
 +
<br>
 +
'''Results:''' The property of a restriction enzymes are all related to its frequency of cutting. The mean number of genes for fragments as well as its variance and the probability of containing essential genes can be derived from that only information.<br>
</div>
</div>
| valign="top" align="center" width="450"|
| valign="top" align="center" width="450"|

Revision as of 15:40, 11 October 2008


Overview on the modelling framework

This page is meant to give an introduction to the the overall modelling framework we have constructed in order to asses feasibility analysis, temporal scale details and other parameter estimations that regard our project setup. As introduced in the project overview section, four main components can be identified in the deviced mechanism. Accordingly, we divided the modelling framework in four modules that tackles the relative problematics.
The first module is concerned with the analysis of restriction enzymes and their cutting pattern on E.Coli genome, the second module predict the cell's response to the selection pressure and the forced genome reduction from a system point of view (that is, using a genome scale model), the third module addresses issues related to the sensitivity and setting of the chemostat mechanism, the fourth and final module presents the mathematic model of the genetic switch circuit used to control the restriction enzymes expression.
In the table below, you can find a bird-eye view on the four modules, with the most important aspects highlighted. Since we believe that a model is useful only when it answers specific and well-posed questions, this is the first aspect we report in the summary view. Second we briefly report about the modelling method applied. As last, we summarize the results we obtained. By clicking on each module's title, you can browse the specific module pages containing all the detailed information, such as plots, modelling assumpations and data sources. It is as well possible to download all the data and code (MATLAB source) that we wrote and used in order to generate the results.

Modelling Framework

1) Restriction Enzymes Analysis

RestEnzymesIntro.jpg

Questions:

  • Which are the available cutting patterns?
  • How is the distribution of genes in each fragment related to the frequence of cutting?
  • Is it possible to identify a restriction enzyme that optimize the probability reduced but vital strains?

Method:
E.Coli K12 genome and annotation was digested using 713 different restriction enzymes and statistical analysis applied on the fragment pattern.
Results: The property of a restriction enzymes are all related to its frequency of cutting. The mean number of genes for fragments as well as its variance and the probability of containing essential genes can be derived from that only information.

2) Genome Scale Analysis

GenomeScaleIntro.jpg

Questions:
Method:
Results:

3) Chemostat Selection Method

ChemostatSmallIntro.png

Questions:
Method:
Results:

4) Switch Circuit

Questions:
Method:
Results: