Difference between revisions of "Eukaryotic Models"

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=Eukaryotic Models of Stochasticity in Gene Expression=
 
=Eukaryotic Models of Stochasticity in Gene Expression=
Eukaryotic Models of stochasticity differ from prokaryotic models becuase their processes of transcription and translation are inherently different. Therefore, in  stochastic models, different single variables are needed to account for discrepencies. Collins et. al. created a model for Stochasticity in Eukaryotes, focusing on the stabilization of the transcriptional complex to mRNA. Where states PC1, PC2, and PC3 all detail different states of DNA. PC1 represents the inactive DNA, PC2 represents an intermediate complex where TATA binding protein and other transcriptional factors are bound, and PC3 represents the preinitiation complex. Another characterization of Eukaryotic expression lies in the alpha variable which represents masking and unmasking of DNA by chromatin structure (Collins et. al., 2003).  
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Eukaryotic Models of stochasticity differ from prokaryotic models becuase their processes of transcription and translation are inherently different. Therefore, in  stochastic models, different single variables are needed to account for discrepencies. Collins et. al. created a model for Stochasticity in eukaryotes which represented factors in the stabilization of the transcriptional complex to mRNA (Figure 1). In Figure 1, states PC1, PC2, and PC3 all detail different states of DNA. PC1 represents the inactive DNA, PC2 represents an intermediate complex where TATA binding protein and other transcriptional factors are bound, and PC3 represents the preinitiation complex. Another characterization of Eukaryotic expression lies in the alpha variable which represents masking and unmasking of DNA by chromatin structure (Collins et. al., 2003).  
 
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Revision as of 14:59, 6 December 2007

Eukaryotic Models of Stochasticity in Gene Expression

Eukaryotic Models of stochasticity differ from prokaryotic models becuase their processes of transcription and translation are inherently different. Therefore, in stochastic models, different single variables are needed to account for discrepencies. Collins et. al. created a model for Stochasticity in eukaryotes which represented factors in the stabilization of the transcriptional complex to mRNA (Figure 1). In Figure 1, states PC1, PC2, and PC3 all detail different states of DNA. PC1 represents the inactive DNA, PC2 represents an intermediate complex where TATA binding protein and other transcriptional factors are bound, and PC3 represents the preinitiation complex. Another characterization of Eukaryotic expression lies in the alpha variable which represents masking and unmasking of DNA by chromatin structure (Collins et. al., 2003).



Figure 1
400px-Eukaryotic stochastic model.jpg

Figure 1 was obtained at http://www.nature.com/nature/journal/v422/n6932/abs/nature01546.html permission pending
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