Difference between revisions of "Origins and Characterization of Stochasticity"
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− | <center>[[ | + | <center>[[Term_paper_wiki| <span style="color:red">Home</span>]] | [[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>]]</center> |
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Revision as of 17:26, 6 December 2007
In Depth | Overview of the Origins and Characterization of Stochasticity | ||
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Finite Number Effect
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Manifestations of stochasticity in cellular protein production are observable in processes both intrinsic and extrinsic to the gene in question. Intrinsic stochastic processes are characterized as those which are inherent in transcription and translation (e.g. Gillsepe Model); extrinsic stochastic processes are characterized as those which arises from sources other than the gene in question (e.g. Presence of RNAP/ribosomes/mRNA degradation machinery, stage in cell cycle, or plasmid copy number). While stochasticity in protein production comes from a variety sources, many labs have sought to distinguish dominant sources from negligible ones. Different experimental parameters and independent variables aside, there are underlying motifs in the characterization of stochasticity between studies.
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