Team:Exeter/Modelling

Introduction

Our model predicts how the absorbtion spectrum of a modified E.Coli changes over time in response to a given incident light spectrum. It is used to estimate key properties of our system such as stability, development time of image, the balance of colours and has three steps to its operation.

Currently the model is based on results from literature and theoretical conjecture as experimental results are not available. The motivation for the model was to numerically characterize our bio-bricks for future use and to help us create the first colour coliroid. With experimental results the model could readily be updated to fulfill its original mandate.

The Team

We are Exeter iGEM's dry team. Together we are responsible for the creation and development of a working model of our system and other various tasks

Angus Laurenson Physics

Callum Vincent Physics

Henri Laakso Electrical Engineering

Modelling Software

The model uses two programs; [http://www.mathworks.co.uk/products/matlab/ MATLAB] and KaSiM combined using a batch file.

KaSiM is a [http://en.wikipedia.org/wiki/Stochastic stochastic] simulator that executes files written in [http://www.kappalanguage.org/ Kappa]. Kappa is a rule based modeling language for protein interaction networks.

MATLAB® is a high-level language and interactive environment for numerical computation, visualization, and programming. It can be used to analyze data, develop algorithms, and create models and applications.

Together they provide the necessary tools to create an accurate model of our bio-camera system.

The model

This section will go into detail about the workings of the model.

Sensor activation rate

This subsection will explain how the activation rate of sensors is determined and provide some justification of the method

Kappa model

This subsection will explain the kappa model. How it works, the justification for its use,

Absorbtion spectrum

This subsection will explain how the absorbtion spectrum of the cell is calculated and justify the method.

Assumptions

Due to the complexity of biological systems our model will include but not be limited to the following assumptions:

• Classical elastic mechanics
• Bacteria contain a homogeneous mix of components
• All constituents move with brownian motion
• Bacteria are identical
• Bacteria evenly distributed across surface
• Bacteria do not interact
• Only pathway specific species are rate limiting