Team:Grenoble/Modeling/Amplification/Stochastic

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<a href="https://2012.igem.org/wiki/index.php?title=Team:Grenoble/Modeling/Amplification/ODE"><img src="https://static.igem.org/mediawiki/2012/e/ef/ODE.png" alt="" /></a>
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<a href="https://2012.igem.org/wiki/index.php?title=Team:Grenoble/Modeling/Amplification/Sensitivity"><img src="https://static.igem.org/mediawiki/2012/a/a4/Sensitivity_and_parameters.png" alt="" /></a>
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<a href="https://2012.igem.org/wiki/index.php?title=Team:Grenoble/Modeling/Amplification/Quorum"><img src="https://static.igem.org/mediawiki/2012/6/65/Quorum_Sensing.png" alt="" /></a>
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<a href="https://2012.igem.org/wiki/index.php?title=Team:Grenoble/Modeling/Amplification/Stochastic"><img src="https://static.igem.org/mediawiki/2012/a/ad/Stochastic_analysis.png" alt="" /></a>
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<h1> Goal </h1>
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<a href="https://2012.igem.org/wiki/index.php?title=Team:Grenoble/Modeling/Amplification/Stochastic/what"><img src="https://static.igem.org/mediawiki/2012/d/d9/What.png" alt="" /></a>
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Statistic modeling is a technique of presenting data or predicting outcomes that takes into account a certain degree of randomness or unpredictability. The stochastic process is often used to represent the evolution of some random value, or system, over time.
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<a href="https://2012.igem.org/Team:Grenoble/Modeling/Amplification/Stochastic/results"><img src="https://static.igem.org/mediawiki/2012/1/17/Results.png" alt="" /></a>
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<center><img src="https://static.igem.org/mediawiki/2012/e/e7/Stochastic_def.png" alt="" /></center>
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It is the probabilistic counterpart to a deterministic process.
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<center><img src="https://static.igem.org/mediawiki/2012/3/38/Diagram_stoch.png" alt="" /></center>
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<h1> Why </h1>
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Latest revision as of 16:57, 23 September 2012

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