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Team:Grenoble/Modeling/Introduction
From 2012.igem.org
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| - | + | <h1>Overview</h1> | |
| - | </a> | + | To model the system, we divided it into <a href="https://2012.igem.org/Team:Grenoble/Biology/Introduction#scheme">three modules</a>: |
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| + | <a href="https://2012.igem.org/Team:Grenoble/Modeling/Signaling" style="font-size: 1.2em;"><img src="https://static.igem.org/mediawiki/2012/4/49/1_mod.png" alt="" />Signaling module </a> | ||
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| + | In this part we used a deterministic model to determine the sensitivity of the sensor. This analysis enabled us to know that the amplification module is required for the incoming signal to drive the subsequent modules. | ||
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| - | + | <a href="https://2012.igem.org/Team:Grenoble/Modeling/Amplification" style="font-size: 1.2em;"><img src="https://static.igem.org/mediawiki/2012/1/1e/2_mod.png" alt="" />Internal amplification module</a> | |
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| + | We first used deterministic model to evaluate the sensitivity of the amplification loop and determine the response time. A steady state analysis was performed to understand how the system works. | ||
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| - | + | <a href="https://2012.igem.org/Team:Grenoble/Modeling/Amplification/Quorum" style="font-size: 1.2em;"><img src="https://static.igem.org/mediawiki/2012/5/57/3_mod.png" alt="" />External amplification and communication</a> | |
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| - | + | Then, we studied the communication between the bacteria to evaluate the time collective response time of a bacterial population as a whole. | |
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| - | + | Because we know that the production of protein is not always turned on or turned off, this can lead to false positives/negatives. We also evaluated the false positives rate of our sensor using a stochastic model. | |
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Latest revision as of 02:54, 27 September 2012
Overview
To model the system, we divided it into three modules:
Signaling module
In this part we used a deterministic model to determine the sensitivity of the sensor. This analysis enabled us to know that the amplification module is required for the incoming signal to drive the subsequent modules.
Internal amplification module
We first used deterministic model to evaluate the sensitivity of the amplification loop and determine the response time. A steady state analysis was performed to understand how the system works.
External amplification and communication
Then, we studied the communication between the bacteria to evaluate the time collective response time of a bacterial population as a whole.
Because we know that the production of protein is not always turned on or turned off, this can lead to false positives/negatives. We also evaluated the false positives rate of our sensor using a stochastic model.
