Difference between revisions of "Team:SJTU-BioX-Shanghai/Signal Pathway"

Line 102: Line 102:
 
                         <p>Our model helps describe intracellular interactions of our multifactorial visualized detection system. We also use it to analyze and evaluate our synthetic biology system. The model was built using Simbiology, a MATLAB toolbox.</p>
 
                         <p>Our model helps describe intracellular interactions of our multifactorial visualized detection system. We also use it to analyze and evaluate our synthetic biology system. The model was built using Simbiology, a MATLAB toolbox.</p>
 
<p>From these figures, we find several typical patterns of species variation. And the result(链接) of our experiments also fits these patterns well.</p>
 
<p>From these figures, we find several typical patterns of species variation. And the result(链接) of our experiments also fits these patterns well.</p>
   <div class="my-title h5-my-responsive" id="section1">Signal Pathway Model</div>
+
   <div class="my-title h5-my-responsive" id="section1">Pathway Illustration</div>
                        <p>Pathway Illustration:</p>
+
           
 
                         <div class="figure-intro">
 
                         <div class="figure-intro">
 
                             <img src="https://static.igem.org/mediawiki/2017/6/6f/Pathw1.png" class="img-fluid">
 
                             <img src="https://static.igem.org/mediawiki/2017/6/6f/Pathw1.png" class="img-fluid">
 
                             <div class="figure-text"><strong>Figure1: Signal Pathway construct</strong>Inducers enters the cell, activates receptor and binding with repressor protein, leading to antisense producing. Then antisense binds with STAR. Finally sfGFP expression starts.</div>
 
                             <div class="figure-text"><strong>Figure1: Signal Pathway construct</strong>Inducers enters the cell, activates receptor and binding with repressor protein, leading to antisense producing. Then antisense binds with STAR. Finally sfGFP expression starts.</div>
 
                         </div>
 
                         </div>
                        <p>Simulation Results:</p>
+
<div class="my-title h5-my-responsive" id="section1">Simulation Results</div>
 
                         <div class="figure-intro">
 
                         <div class="figure-intro">
 
                             <img src="https://static.igem.org/mediawiki/2017/a/ac/SFDG.png" class="img-fluid">
 
                             <img src="https://static.igem.org/mediawiki/2017/a/ac/SFDG.png" class="img-fluid">
Line 131: Line 131:
 
                     <div class="col-lg-1">
 
                     <div class="col-lg-1">
 
                     </div>
 
                     </div>
                   
+
                <div class="my-title h5-my-responsive" id="section1">Parameters</div> 
 
                         <div class="figure-intro">
 
                         <div class="figure-intro">
 
                             <table class="table table-res table-res2 table-hover" align="center">
 
                             <table class="table table-res table-res2 table-hover" align="center">

Revision as of 20:50, 1 November 2017

Signal Pathway
Signal Pathway Model

Our model helps describe intracellular interactions of our multifactorial visualized detection system. We also use it to analyze and evaluate our synthetic biology system. The model was built using Simbiology, a MATLAB toolbox.

From these figures, we find several typical patterns of species variation. And the result(链接) of our experiments also fits these patterns well.

Pathway Illustration
Figure1: Signal Pathway constructInducers enters the cell, activates receptor and binding with repressor protein, leading to antisense producing. Then antisense binds with STAR. Finally sfGFP expression starts.
Simulation Results
Figure2: sfGFP degradation over time.
Figure3: antiSTAR1 variation over time.
Figure4: STAR & STAR_complex variation over time.
Figure5: sfGFP& STAR_complex variation over time.

From these figures, we find several typical patterns of species variation. And the result(链接) of our experiments also fits these patterns well.

Parameters
Parameters Reaction Value Reaction Type
maxVproduceAsRprotein AsrR + RNA_polymerase -> AsrR + RNA_polymerase + AsrR_protein 0.6 MassAction
RNApolyConstant All Reaction with Polymerase 1
kr_AsR_complex As + AsrR_protein <-> AsR_complex 0.8 MassAction
kf_AsR_complex As + AsrR_protein <-> AsR_complex 0.05 MassAction
maxVproduceanti RNA_polymerase + Promoter_STAR1 -> RNA_polymerase + Promoter_STAR1 + antiSTAR1 60 Competitive-Inhibition
AsrRproteinRepressConstant RNA_polymerase + Promoter_STAR1 -> RNA_polymerase + Promoter_STAR1 + antiSTAR1 10 Competitive-Inhibition
kf_STAR1complex antiSTAR1 + STAR1 <-> STAR1_complex 50 MassAction
kr_STAR1complex antiSTAR1 + STAR1 <-> STAR1_complex 0.8 MassAction
maxVproducesfGFP Promoter_target + RNA_polymerase -> Promoter_target + RNA_polymerase + sfGFP 100 Competitive-Inhibition
antiRepressConstant Promoter_target + RNA_polymerase -> Promoter_target + RNA_polymerase + sfGFP 10 Competitive-Inhibition
kd_AsrR AsrR -> null 0.007 MassAction
kd_RNA_polymerase RNA_polymerase -> null 0.007 MassAction
kd_AsrR_protein AsrR_protein -> null 0.007 MassAction
kd_antiSTAR antiSTAR1 -> null 0.007 MassAction
kd_STAR STAR1 -> null 0.007 MassAction
kd_STARcomplex STAR1_complex -> null 0.007 MassAction
kd_sfGFP sfGFP -> null 0.007 MassAction
Table1