Team:ETH Zurich/Modeling/Overview
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<h1>The digital bacterial-based minesweeper</h1> | <h1>The digital bacterial-based minesweeper</h1> | ||
- | <p align="justify" | + | <p align="justify">We developed a 2D spatio-temporal model of the Colisweeper bacterial game to evaluate our network, validate the design and get some insights of how we can improve our system. Essentially, we studied the diffusion of [https://2013.igem.org/Team:ETH_Zurich/Experiments_2 OHHL] in a hexagonal grid setup with mine and non-mine colonies. To solve the system of partial differential equations we used finite element methods, and simulations were carried out in Comsol Multiphysics. Most initial model parameters are taken from literature supported by experimental evidence, and we continually refine their accuracy for our system by estimating them from our own experimental data. It needs to be mentioned that there was a close interplay with the model and experiments in our project which facilitated the refining of our system. Based on this premise, we generate data from experiments to validate the model, but also use the model to predict the behavior of our system and help further experimental designs. <br></p> |
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Revision as of 02:07, 5 October 2013
The digital bacterial-based minesweeper
We developed a 2D spatio-temporal model of the Colisweeper bacterial game to evaluate our network, validate the design and get some insights of how we can improve our system. Essentially, we studied the diffusion of OHHL in a hexagonal grid setup with mine and non-mine colonies. To solve the system of partial differential equations we used finite element methods, and simulations were carried out in Comsol Multiphysics. Most initial model parameters are taken from literature supported by experimental evidence, and we continually refine their accuracy for our system by estimating them from our own experimental data. It needs to be mentioned that there was a close interplay with the model and experiments in our project which facilitated the refining of our system. Based on this premise, we generate data from experiments to validate the model, but also use the model to predict the behavior of our system and help further experimental designs.
Note: For parameter values and references click on the parameter of interest or have a look at the parameters section.