Team:Dundee/Modeling
From 2014.igem.org
Line 157: | Line 157: | ||
</a> | </a> | ||
+ | |||
+ | </div> | ||
+ | </div> | ||
+ | |||
+ | <p> | ||
+ | Equation (1) was then analysed in MAPLE for varying PQS concentrations using the parameters in table 1. | ||
+ | </p> | ||
</div> | </div> | ||
</div> | </div> | ||
+ | |||
+ | |||
<hr> | <hr> | ||
<h2 id="3">Final Prototype</h2> | <h2 id="3">Final Prototype</h2> |
Revision as of 13:28, 4 October 2014
Modeling
Maths.. maths is boring
Modeling and Analysis of Signaling Pathways
Methodology
The models for each system were developed using three different approaches. As shown in figure 1 each of the approaches; ordinary differential equations (ODEs), stochastic simulation algorithm (SSA) and NetLogo, provided a different understanding of each system.
Sigmoidal Expression of mCherry in PQS System
When the PQS system was induced with synthetic PQS, no mCherry was expressed and so the wet team sought the advice of the dry team to find out why and how the situation could be resolved.
After constructing a series of ordinary differential equations (full derivation can be found in the appendix) we established the following relationship between PQS (Se) and mCherry:
Equation (1) was then analysed in MAPLE for varying PQS concentrations using the parameters in table 1.
Final Prototype