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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 <section>
-<h1> Goal </h1>
+<center>
-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.
+<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>
+<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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