Team:Carnegie Mellon/Modelling

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                 The model will be composed in Matlab. It incorporates file input/output to retrieve measurement data (or approximations of data) to approximate two important characteristics of gene expression, PoPS and translational efficiency. The inputs to the model will be time dependent fluorescence measurements of mRNA and protein. Four time dependent measurements are needed: mRNA fluorescence during synthesis, mRNA fluorescence during degradation (no mRNA production), protein fluorescence during synthesis, and protein fluorescence during degradation (no protein production). Other constants, such as concentrations of the dyes that are put into the cells, can also be input into the model in order to increase precision of the outputs. However, these can be approximated with previously measured values if for some reason they cannot be determined.  
                 The model will be composed in Matlab. It incorporates file input/output to retrieve measurement data (or approximations of data) to approximate two important characteristics of gene expression, PoPS and translational efficiency. The inputs to the model will be time dependent fluorescence measurements of mRNA and protein. Four time dependent measurements are needed: mRNA fluorescence during synthesis, mRNA fluorescence during degradation (no mRNA production), protein fluorescence during synthesis, and protein fluorescence during degradation (no protein production). Other constants, such as concentrations of the dyes that are put into the cells, can also be input into the model in order to increase precision of the outputs. However, these can be approximated with previously measured values if for some reason they cannot be determined.  
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The output values, PoPS and translational efficiency, will help characterize promoters that will be used in the experiments. These parameters are notoriously difficult to measure in vivo. In addition to the two main output values, the model also calculates other characteristics of the cell, such as degradation constants for mRNA and protein, and transcriptional efficiency.  
The output values, PoPS and translational efficiency, will help characterize promoters that will be used in the experiments. These parameters are notoriously difficult to measure in vivo. In addition to the two main output values, the model also calculates other characteristics of the cell, such as degradation constants for mRNA and protein, and transcriptional efficiency.  

Revision as of 19:16, 11 July 2012

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Project Description

The model will be composed in Matlab. It incorporates file input/output to retrieve measurement data (or approximations of data) to approximate two important characteristics of gene expression, PoPS and translational efficiency. The inputs to the model will be time dependent fluorescence measurements of mRNA and protein. Four time dependent measurements are needed: mRNA fluorescence during synthesis, mRNA fluorescence during degradation (no mRNA production), protein fluorescence during synthesis, and protein fluorescence during degradation (no protein production). Other constants, such as concentrations of the dyes that are put into the cells, can also be input into the model in order to increase precision of the outputs. However, these can be approximated with previously measured values if for some reason they cannot be determined.

The output values, PoPS and translational efficiency, will help characterize promoters that will be used in the experiments. These parameters are notoriously difficult to measure in vivo. In addition to the two main output values, the model also calculates other characteristics of the cell, such as degradation constants for mRNA and protein, and transcriptional efficiency.

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