Difference between revisions of "Glycine 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 0.00000803 and 8.03. So the mean is 4.01 and standard deviation would be 2.007.  
 
{|class="wikitable"
 
{|class="wikitable"
 
! Parameter
 
! Parameter
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|<math>K_{1}</math>
 
|<math>K_{1}</math>
|Sampled between 0.00000803 and 8.03
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|<math>4.01 \pm 2.007</math>
 
|rowspan="2"|
 
|rowspan="2"|
 
|rowspan="2"|
 
|rowspan="2"|
 
|-
 
|-
 
|<math>K_{2}</math>
 
|<math>K_{2}</math>
|Sampled between 0.00000803 and 8.03
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|<math>4.01 \pm 2.007</math>
 
|}
 
|}
 
  
 
==References==
 
==References==
 
<references/>
 
<references/>

Latest revision as of 17:19, 23 May 2014

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

Reaction equation

 Glycine \leftrightarrow Glycine_{out}

Rate equation

Simple mass action rate law is used.

 v = K_{1} * [Glycine] - K_{2} * [Glycine_{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} 8.03 \times 10^{-3} [1] S^{-1} Escherichia coli
K_{2} 8.03 \times 10^{-3} 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 0.00000803 and 8.03. So the mean is 4.01 and standard deviation would be 2.007.
Parameter Value Organism Remarks
K_{1} 4.01 \pm 2.007
K_{2} 4.01 \pm 2.007

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