Difference between revisions of "Serine out"

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(Parameters with uncertainty)
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==Parameters with uncertainty==
 
==Parameters with uncertainty==
*The transport rates have been modelled using mass action kinetics (i.e., as non-saturable, non-enzymatic reactions). No information is available about the uncertainty of these parameters. As these parameters are strictly positive, they are sampled using a log-normal distribution as are and values. The means of <math>K_{1}</math> are set to the value reported in Turnaev (2006) et al. <ref name="Turnaev_2006"></ref> for the fixed-parameter model. The reaction is presumed to be at equilibrium, such that <math>K_{eq} = 1</math> and <math>K_{1} = K_{2}</math>. The sampling of the parameters are done in a way so that it ranges between <math>[0.001\times mean \quad 1000 \times mean  ]</math> to allow a large exploration of the parameter space.
+
*The transport rates have been modelled using mass action kinetics (i.e., as non-saturable, non-enzymatic reactions). No information is available about the uncertainty of these parameters. As these parameters are strictly positive, they are sampled using a log-normal distribution as are and values. The means of <math>K_{1}</math> are set to the value reported in Turnaev (2006) et al. <ref name="Turnaev_2006"></ref> for the fixed-parameter model. The reaction is presumed to be at equilibrium, such that <math>K_{eq} = 1</math> and <math>K_{1} = K_{2}</math>. The sampling of the parameters are done in a way so that it ranges between <math>[0.001\times mean \quad 1000 \times mean  ]</math> to allow a large exploration of the parameter space. We use the '''Range rule''' to calculate the mean and standard deviation from maximum and minimum value. For both <math>K_{1}</math> and <math>K_{2}</math> the minimum and maximum value lies between 0.0000103 and 10.3. So the mean is 5.16 and standard deviation would be 2.57499.  
 
{|class="wikitable"
 
{|class="wikitable"
 
! Parameter
 
! Parameter
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|-
 
|-
 
|<math>K_{1}</math>
 
|<math>K_{1}</math>
|Sampled between 0.0000103 and 10.3
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|5.16 \pm 2.57
 
|rowspan="2"|
 
|rowspan="2"|
 
|rowspan="2"|
 
|rowspan="2"|
 
|-
 
|-
 
|<math>K_{2}</math>
 
|<math>K_{2}</math>
|Sampled between 0.0000103 and 10.3
+
|5.16 \pm 2.57
 
|}
 
|}
  
 
==References==
 
==References==
 
<references/>
 
<references/>

Revision as of 17:14, 23 May 2014

This reaction describes the utilization of the endproduct Serine in other pathways.

Reaction equation

 Serine \leftrightarrow Serine_{out}

Rate equation

Simple reversible mass action rate law is used.

 v = K_{1} * [Serine] - K_{2} * [Serine_{out}]

Parameters

  • For Transport reactions it is presumed to be at equilibrium, such that K_{eq} = 1 and K_{1} = K_{2}.
Parameter Value Units Organism Remarks
K_{1} 0.0103 [1] S^{-1} Escherichia coli
K_{2} 0.0103 S^{-1}

Parameters with uncertainty

  • The transport rates have been modelled using mass action kinetics (i.e., as non-saturable, non-enzymatic reactions). No information is available about the uncertainty of these parameters. As these parameters are strictly positive, they are sampled using a log-normal distribution as are and values. The means of K_{1} are set to the value reported in Turnaev (2006) et al. [1] for the fixed-parameter model. The reaction is presumed to be at equilibrium, such that K_{eq} = 1 and K_{1} = K_{2}. The sampling of the parameters are done in a way so that it ranges between [0.001\times mean \quad 1000 \times mean  ] to allow a large exploration of the parameter space. We use the Range rule to calculate the mean and standard deviation from maximum and minimum value. For both K_{1} and K_{2} the minimum and maximum value lies between 0.0000103 and 10.3. So the mean is 5.16 and standard deviation would be 2.57499.
Parameter Value Organism Remarks
K_{1} 5.16 \pm 2.57
K_{2} 5.16 \pm 2.57

References

  1. 1.0 1.1 Turnaev II, Ibragimova SS, Usuda Y et al (2006). Mathematical modeling of serine and glycine synthesis regulation in Escherichia coli. Proceedings of the fifth international conference on bioinformatics of genome regulation and structure 2:78–83