Team:Paris/Analysis/Construction2
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We are interested to understand the factors that account for an oscillating behaviour at population level. We build two models to study systems that are equipated with quorum sensing capabilities but that relay on different designs principles. The proposed models are: | We are interested to understand the factors that account for an oscillating behaviour at population level. We build two models to study systems that are equipated with quorum sensing capabilities but that relay on different designs principles. The proposed models are: | ||
- | *In the one model, we use a modular design. We consider that the core system is one of the modules of the system. In adittion, the other module is an two gene oscillator system presented in [[Team:Paris/Modeling/BOB#Bibliography|[Garcia-Ojalvo]]] that accounts for quorum sensing. | + | *In the one model, we use a modular design. We consider that the core system is one of the modules of the system. In adittion, the other module is an two gene oscillator system presented in [[Team:Paris/Modeling/BOB#Bibliography|[Garcia-Ojalvo]]] that accounts for quorum sensing. We call this alternative the 'bimodular system'. |
- | *In the other model, we rewire the architecture of the core system to have the desired functionality of the system in a single circuit. | + | *In the other model, namely the 'unimodular system', we rewire the architecture of the core system to have the desired functionality of the system in a single circuit. |
- | Both the | + | Both the bimodular and unimodular models describe events that happend not only at the cellular level (as in the core system) but also at the population level due to interactions needed bettwen a cell and its environment during quorum sensing. |
In the following sections, we first describe the population modeling (the common part amoung our two proposed models) to then focus our attention to the characteristics that are exclusive to each of the modeling alternatives. | In the following sections, we first describe the population modeling (the common part amoung our two proposed models) to then focus our attention to the characteristics that are exclusive to each of the modeling alternatives. | ||
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* We assume a logistic model to determine bacteria growth in the chemostat, in agreement with standar procedures (reference). This hypothesis implies that bacteria growth rate has to be proportional to the existing bacteria population size and to the amount of available resources in the medium. | * We assume a logistic model to determine bacteria growth in the chemostat, in agreement with standar procedures (reference). This hypothesis implies that bacteria growth rate has to be proportional to the existing bacteria population size and to the amount of available resources in the medium. | ||
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* As discussed [[Team:Paris/Network_analysis_and_design/System_improvements|previously]], we choose to use quorum sensing as a way to improve the oscillating behaviour of our [[Team:Paris/Network_analysis_and_design/Core_system|core system]] and, at the same time, as a way to archeive population synchronization. When a cultive of bacteria is synchronized, it means that every single cell express in average the same genes in unison. As a result, a maximum level of fluorescense is obtained. | * As discussed [[Team:Paris/Network_analysis_and_design/System_improvements|previously]], we choose to use quorum sensing as a way to improve the oscillating behaviour of our [[Team:Paris/Network_analysis_and_design/Core_system|core system]] and, at the same time, as a way to archeive population synchronization. When a cultive of bacteria is synchronized, it means that every single cell express in average the same genes in unison. As a result, a maximum level of fluorescense is obtained. | ||
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+ | == Description == | ||
<CENTER> | <CENTER> |
Revision as of 19:19, 27 October 2008
Model Construction
MotivationWe are interested to understand the factors that account for an oscillating behaviour at population level. We build two models to study systems that are equipated with quorum sensing capabilities but that relay on different designs principles. The proposed models are:
Both the bimodular and unimodular models describe events that happend not only at the cellular level (as in the core system) but also at the population level due to interactions needed bettwen a cell and its environment during quorum sensing. In the following sections, we first describe the population modeling (the common part amoung our two proposed models) to then focus our attention to the characteristics that are exclusive to each of the modeling alternatives.
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Description
Parameters Searchmanly from literature but also from S0 analysis.
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