Difference between revisions of "Team:Paris Bettencourt/Model"
Alma.chapet (Talk | contribs) |
|||
| Line 110: | Line 110: | ||
<div class="divseparator"></div> | <div class="divseparator"></div> | ||
| − | <h1 id=thirdmodel> | + | <h1 id=thirdmodel>Logic circuit modeling</h1> |
| − | + | ||
| − | + | <div class=text1>Recent work on transcription elements showed that assembling insulated synthetic operator upstream and downstream of a insulated T7 promoter core allowed for a more diverse control of gene expression and a more specific response time (Zong et al., 2017). </br> More importantly, the expression of a gene regulated by such repressible promoters can be well-described by a simple equation:</br> | |
| − | + | ||
| − | + | <img src="https://2017.igem.org/File:Alma_eq1_PB.png"><div> | |
| − | + | ||
| − | + | <div class=text2><div class=text2left>α, β , η<sub>A</sub>, K<sub>A</sub> are respectively the maximal and basal promoter activity, the Hill coefficient and the dissociation constant of the transcriptional activator-promoter core pair. η<sub>R</sub> and Κ<sub>R</sub> represent the Hill coefficient and dissociation constant of the binding of a repressor to its cognate operator. δ<sub>R</sub> represents the relaxation time, the expected time in which an operator is not bound to any repressor. </div> | |
| − | + | ||
| − | + | <div class=text2right>Making the assumption that the elements are insulated, we can easily combine them to create not single but dually repressible promoters, and predict their performance by generalising equation 1. In Equation (2), the fact that more than one repressor type binding to the promoter was taken into account and changes to relaxation time and the number of total microstates in the equilibrium were made accordingly.</div></div> | |
| − | + | ||
| − | + | <img src="https://2017.igem.org/File:Alma_eq2_PB.png"> | |
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
</div> | </div> | ||
</div> | </div> | ||
Revision as of 02:33, 1 November 2017
MODELLING
OPTIC MODEL
your text
RNA is a light cost nucleotide material in the cell,
We aim to recreate RNA agglomerations as formed
in mammalian cells with triple repeat disorders,
which show liquid phase separation, forming a
organelle-like vesicle, where local concentrations of
enzymes can be created.
RNA is a light cost nucleotide material in the cell,
We aim to recreate RNA agglomerations as formed
in mammalian cells with triple repeat disorders,
which show liquid phase separation, forming a
organelle-like vesicle, where local concentrations of
enzymes can be created.
RNA is a light cost nucleotide material in the cell,
We aim to recreate RNA agglomerations as formed
in mammalian cells with triple repeat disorders,
which show liquid phase separation, forming a
organelle-like vesicle, where local concentrations of
enzymes can be created.
RNA is a light cost nucleotide material in the cell,
We aim to recreate RNA agglomerations as formed
in mammalian cells with triple repeat disorders,
which show liquid phase separation, forming a
organelle-like vesicle, where local concentrations of
enzymes can be created.
SECOND MODEL
your text
RNA is a light cost nucleotide material in the cell,
We aim to recreate RNA agglomerations as formed
in mammalian cells with triple repeat disorders,
which show liquid phase separation, forming a
organelle-like vesicle, where local concentrations of
enzymes can be created.
RNA is a light cost nucleotide material in the cell,
We aim to recreate RNA agglomerations as formed
in mammalian cells with triple repeat disorders,
which show liquid phase separation, forming a
organelle-like vesicle, where local concentrations of
enzymes can be created.
RNA is a light cost nucleotide material in the cell,
We aim to recreate RNA agglomerations as formed
in mammalian cells with triple repeat disorders,
which show liquid phase separation, forming a
organelle-like vesicle, where local concentrations of
enzymes can be created.
RNA is a light cost nucleotide material in the cell,
We aim to recreate RNA agglomerations as formed
in mammalian cells with triple repeat disorders,
which show liquid phase separation, forming a
organelle-like vesicle, where local concentrations of
enzymes can be created.
Logic circuit modeling
Recent work on transcription elements showed that assembling insulated synthetic operator upstream and downstream of a insulated T7 promoter core allowed for a more diverse control of gene expression and a more specific response time (Zong et al., 2017). More importantly, the expression of a gene regulated by such repressible promoters can be well-described by a simple equation:
α, β , ηA, KA are respectively the maximal and basal promoter activity, the Hill coefficient and the dissociation constant of the transcriptional activator-promoter core pair. ηR and ΚR represent the Hill coefficient and dissociation constant of the binding of a repressor to its cognate operator. δR represents the relaxation time, the expected time in which an operator is not bound to any repressor.
Making the assumption that the elements are insulated, we can easily combine them to create not single but dually repressible promoters, and predict their performance by generalising equation 1. In Equation (2), the fact that more than one repressor type binding to the promoter was taken into account and changes to relaxation time and the number of total microstates in the equilibrium were made accordingly.
Centre for Research and Interdisciplinarity (CRI)
Faculty of Medicine Cochin Port-Royal, South wing, 2nd floor
Paris Descartes University
24, rue du Faubourg Saint Jacques
75014 Paris, France
bettencourt.igem2017@gmail.com
bettencourt.igem2017@gmail.com 
