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=Stochasticity in Gene Expression=

! colspan="3" style="color: black; background-color: red;" width="60%"| <font size="+1">Introduction</font>

[[Origins and Characterization of Stochasticity|<span style="color:red">Origins and Characterization of Stochasticity</span>]]

[[Modeling Stochasticity|<span style="color:red">Modeling Stochasticity</span>]]

[[Manipulation of Stochasticity|<span style="color:red">Manipulation of Stochasticity</span>]]

[[Evolved Stochasticity?|<span style="color:red">Evolved Stochasticity?</span>]]

[[Concluding Remarks|<span style="color:red">Concluding Remarks</span>]]

[[Citations|<span style="color:red">Citations</span>]]

|<br> <center>[[Image:Sblogo-small.jpg| 350 px]] <br>Image from Synthetic Biology 2.0 http://pbd.lbl.gov/sbconf/agenda.php permission pending</center><br>The goal of synthetic biology is to create synthetic biological constructs from an engineering perspective. Synthetic biology has implications in many fields such as healthcare, fuel production, and data processing. An exciting component of the field is its integration of biology, chemistry, mathematics and computer science; in order to construct devices from the bottom up, synthetic teams have to be able to amalgamate knowledge from many different fields. Problems arise however when synthetic biologists regard synthetic devices as analogous to electronic circuitry. The stochastic nature of biological processes lead to heterogenic responses for a single input. While these stochastic processes pose a problem for synthetic biology they do not prohibit the successful construction of synthetic biological devices all together. This is because characterization of stochastic processes can lead to dry lab design strategies for implementation <i>in vivo</i>. Here is a characterization of the origin of stochasticity, the devices used to model stochasticity, the effect of stochasticity in gene networks, and a section on why stochastic processes might exist in the cell.  

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