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BIOMD0000000229 - Ma2002_cAMP_oscillations

 

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Reference Publication
Publication ID: 12482327
Ma L, Iglesias PA.
Quantifying robustness of biochemical network models.
BMC Bioinformatics 2002 Dec; 3: 38
Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD USA. lma@jhu.edu  [more]
Model
Original Model: BIOMD0000000229.origin
Submitter: Vijayalakshmi Chelliah
Submission ID: MODEL0606755064
Submission Date: 18 Aug 2009 15:46:00 UTC
Last Modification Date: 08 Apr 2016 16:03:22 UTC
Creation Date: 18 Aug 2009 15:45:28 UTC
Encoders:  Vijayalakshmi Chelliah
   Lan Ma
set #1
bqbiol:isVersionOf Gene Ontology cAMP-mediated signaling
Gene Ontology chemotaxis
bqbiol:hasTaxon Taxonomy Dictyostelium discoideum
set #2
bqbiol:hasPart KEGG Pathway Bacterial chemotaxis - Xanthomonas campestris pv. campestris ATCC 33913
set #3
bqmodel:isDerivedFrom BioModels Database Laub1998_SpontaneousOscillations
Notes

This a model from the article:
Quantifying robustness of biochemical network models.
Ma L, Iglesias PA. BMC Bioinformatics.2002 Dec 13;3:38. 12482327,
Abstract:
BACKGROUND: Robustness of mathematical models of biochemical networks is important for validation purposes and can be used as a means of selecting between different competing models. Tools for quantifying parametric robustness are needed. RESULTS: Two techniques for describing quantitatively the robustness of an oscillatory model were presented and contrasted. Single-parameter bifurcation analysis was used to evaluate the stability robustness of the limit cycle oscillation as well as the frequency and amplitude of oscillations. A tool from control engineering--the structural singular value (SSV)--was used to quantify robust stability of the limit cycle. Using SSV analysis, we find very poor robustness when the model's parameters are allowed to vary. CONCLUSION: The results show the usefulness of incorporating SSV analysis to single parameter sensitivity analysis to quantify robustness.


This model is originally proposed by Laub and Loomis (1998).[Laub MT, Loomis WF (1998). A molecular network that produces spontaneous oscillations in excitable cells of Dictyostelium. Mol Biol Cell. 9(12):3521-32. PubMED: 12482327.
The parameters used in this model (Ma and Iglesias, 2002), are different from that used in the original model (Laub and Loomis, 1998), because of the typographical errors in the original paper. The parameters used in the model presented by Ma and Iglesias, are obtained directly from the authors of original publication (Laub and Loomis, 1998). These parameters are also used in the website for the Laub-Loomis model, http://www-biology.ucsd.edu/labs/loomis/network/laubloomis.html.
By using this model, Kim et al., 2006 [Kim J, Bates DG, Postlethwaite I, Ma L, Iglesias PA. (2006) Robustness analysis of biochemical network models. Syst Biol (Stevenage). 153(3):96-104. PubMED: 16984084], validate and extend the analysis approach proposed by Ma and Iglesias (2002), by showing how hybrid optimisation can be used to compute worst-case parameter combinations in the model.


This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2010 The BioModels Team.
For more information see the terms of use.
To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.

Model
Publication ID: 12482327 Submission Date: 18 Aug 2009 15:46:00 UTC Last Modification Date: 08 Apr 2016 16:03:22 UTC Creation Date: 18 Aug 2009 15:45:28 UTC
Mathematical expressions
Reactions
v1 v2 v3 v4
v5 v6 v7 v8
v9 v10 v11 v12
v13 v14    
Physical entities
Compartments Species
compartment ACA CAR1 PKA
incAMP ERK2 REGA
excAMP    
Global parameters
k1 k2 k3 k4
k5 k6 k7 k8
k9 k10 k11 k12
k13 k14    
Reactions (14)
 
 v1  ↔ [ACA];   {CAR1}
 
 v2 [ACA] ↔ ;   {PKA}
 
 v3  ↔ [PKA];   {incAMP}
 
 v4 [PKA] ↔ ;  
 
 v5  ↔ [ERK2];   {CAR1}
 
 v6 [ERK2] ↔ ;   {PKA}
 
 v7  ↔ [REGA];  
 
 v8 [REGA] ↔ ;   {ERK2}
 
 v9  ↔ [incAMP];   {ACA}
 
 v10 [incAMP] ↔ ;   {REGA}
 
 v11  ↔ [excAMP];   {ACA}
 
 v12 [excAMP] ↔ ;  
 
 v13  ↔ [CAR1];   {excAMP}
 
 v14 [CAR1] ↔ ;  
 
   compartment Spatial dimensions: 3.0  Compartment size: 1.0
 
 ACA
Compartment: compartment
Initial concentration: 3.39
 
 CAR1
Compartment: compartment
Initial concentration: 2.45
 
 PKA
Compartment: compartment
Initial concentration: 1.6
 
 incAMP
Compartment: compartment
Initial concentration: 1.2
 
 ERK2
Compartment: compartment
Initial concentration: 1.13
 
 REGA
Compartment: compartment
Initial concentration: 0.9
 
 excAMP
Compartment: compartment
Initial concentration: 0.48
 
Global Parameters (14)
 
   k1
Value: 2.0
Constant
 
   k2
Value: 0.9
Constant
 
   k3
Value: 2.5
Constant
 
   k4
Value: 1.5
Constant
 
   k5
Value: 0.6
Constant
 
   k6
Value: 0.8
Constant
 
   k7
Value: 1.0
Constant
 
   k8
Value: 1.3
Constant
 
   k9
Value: 0.3
Constant
 
   k10
Value: 0.8
Constant
 
   k11
Value: 0.7
Constant
 
   k12
Value: 4.9
Constant
 
   k13
Value: 23.0
Constant
 
   k14
Value: 4.5
Constant
 
Representative curation result(s)
Representative curation result(s) of BIOMD0000000229

Curator's comment: (updated: 18 Aug 2009 16:50:02 BST)

The model reproduces Figure 2 of the reference publication. The model was integrated and simulated using Copasi v4.5 (Build 30)

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