Difference between revisions of "Finite Number Effect"
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The most recognized source of stochasticity in cellular protein production is the finite number effect. The finite number effect states that variability, manifested in the amount of protein production, will increase as the size of the system decreases. A decrease in the size of the system refers to the protein concentration of the cell (the amount of transcriptional machinery that the cell has to work with). | The most recognized source of stochasticity in cellular protein production is the finite number effect. The finite number effect states that variability, manifested in the amount of protein production, will increase as the size of the system decreases. A decrease in the size of the system refers to the protein concentration of the cell (the amount of transcriptional machinery that the cell has to work with). | ||
=Results= | =Results= | ||
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| + | Figure A and B are simulations of the abundance of a reporter protein measured over time(). Figure A details results in a system of a high number of expressed protein and mRNA molecules (3000 and 10000 respectivly). Figure B deails the same simulation however the number of expressed proteins and mRNA molecules was decreased to 30 and 100 molecules respectivly. (100-fold difference.) The histogram on the right of each graph details the probability of a population expressing a respective abundant protein. The fluctuations in the line graph and the broader distribution of population expression in figure b demonstrates the finite number effect. | ||
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[[Image:Protein_level_effects_(vs_determinisitic_equations).png| 500 px]] | [[Image:Protein_level_effects_(vs_determinisitic_equations).png| 500 px]] | ||
Revision as of 23:46, 12 November 2007
What is it
The most recognized source of stochasticity in cellular protein production is the finite number effect. The finite number effect states that variability, manifested in the amount of protein production, will increase as the size of the system decreases. A decrease in the size of the system refers to the protein concentration of the cell (the amount of transcriptional machinery that the cell has to work with).
Results
Figure A and B are simulations of the abundance of a reporter protein measured over time(). Figure A details results in a system of a high number of expressed protein and mRNA molecules (3000 and 10000 respectivly). Figure B deails the same simulation however the number of expressed proteins and mRNA molecules was decreased to 30 and 100 molecules respectivly. (100-fold difference.) The histogram on the right of each graph details the probability of a population expressing a respective abundant protein. The fluctuations in the line graph and the broader distribution of population expression in figure b demonstrates the finite number effect.
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