Model Identifier
BIOMD0000000101
Short description

The model reproduces Fig 5A of the paper. The ligand concentration is increased from 3E-5 to 0.01 at time t=2500 to ensure that the system reaches steady state. Hence, the time t=0 of the paper corresponds to t=2500 in the model. The peak value of the active ligand receptor complex is off by a value of 1.25, the authors have stated that this discrepancy is due to the fact that the figure in the paper corresponds to a slightly different parameter set. The model was successfully tested on MathSBML.


To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.


To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

Format
SBML (L2V1)
Related Publication
  • Signal processing in the TGF-beta superfamily ligand-receptor network.
  • Vilar JM, Jansen R, Sander C
  • PLoS computational biology , 1/ 2006 , Volume 2 , pages: e3 , PubMed ID: 16446785
  • Integrative Biological Modeling Laboratory, Computational Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America. vilar@cbio.mskcc.org
  • The TGF-beta pathway plays a central role in tissue homeostasis and morphogenesis. It transduces a variety of extracellular signals into intracellular transcriptional responses that control a plethora of cellular processes, including cell growth, apoptosis, and differentiation. We use computational modeling to show that coupling of signaling with receptor trafficking results in a highly versatile signal-processing unit, able to sense by itself absolute levels of ligand, temporal changes in ligand concentration, and ratios of multiple ligands. This coupling controls whether the response of the receptor module is transient or permanent and whether or not different signaling channels behave independently of each other. Our computational approach unifies seemingly disparate experimental observations and suggests specific changes in receptor trafficking patterns that can lead to phenotypes that favor tumor progression.
Contributors
Katja Wegner

Metadata information

is
BioModels Database MODEL4023382414
BioModels Database BIOMD0000000101
isDescribedBy
PubMed 16446785
hasTaxon
isVersionOf
Gene Ontology GO:0007179

Curation status
Curated

Tags
Name Description Size Actions

Model files

BIOMD0000000101_url.xml SBML L2V1 representation of Vilar2006_TGFbeta 26.39 KB Preview | Download

Additional files

BIOMD0000000101_urn.xml Auto-generated SBML file with URNs 26.32 KB Preview | Download
BIOMD0000000101.png Auto-generated Reaction graph (PNG) 58.92 KB Preview | Download
BIOMD0000000101-biopax2.owl Auto-generated BioPAX (Level 2) 19.30 KB Preview | Download
BIOMD0000000101.pdf Auto-generated PDF file 175.62 KB Preview | Download
BIOMD0000000101.xpp Auto-generated XPP file 3.18 KB Preview | Download
BIOMD0000000101.m Auto-generated Octave file 5.10 KB Preview | Download
BIOMD0000000101.sci Auto-generated Scilab file 67.00 Bytes Preview | Download
BIOMD0000000101-biopax3.owl Auto-generated BioPAX (Level 3) 28.86 KB Preview | Download
BIOMD0000000101.svg Auto-generated Reaction graph (SVG) 23.61 KB Preview | Download
BIOMD0000000101.vcml Auto-generated VCML file 37.16 KB Preview | Download

  • Model originally submitted by : Katja Wegner
  • Submitted: 22-Mar-2007 22:55:11
  • Last Modified: 05-Jul-2012 15:45:52
Revisions
  • Version: 2 public model Download this version
    • Submitted on: 05-Jul-2012 15:45:52
    • Submitted by: Katja Wegner
    • With comment: Current version of Vilar2006_TGFbeta
  • Version: 1 public model Download this version
    • Submitted on: 22-Mar-2007 22:55:11
    • Submitted by: Katja Wegner
    • With comment: Original import of New Model

(*) You might be seeing discontinuous revisions as only public revisions are displayed here. Any private revisions unpublished model revision of this model will only be shown to the submitter and their collaborators.

Legends
: Variable used inside SBML models


Species
Reactions
Reactions Rate Parameters
=> RII pRII pRII = 4.0
RII => kcd*RII kcd = 0.0277777778
RII_endo => RII kr*RII_endo kr = 0.0333333333333333
RII + RI => lRIRII ka*ligand*RI*RII ka = 1.0; ligand = 3.0E-5
lRIRII => klid*lRIRII klid = 0.25
lRIRII => lRIRII_endo ki*lRIRII ki = 0.3333333333333
=> RI pRI pRI = 8.0
RII => RII_endo ki*RII ki = 0.3333333333333
lRIRII_endo => RI + RII kr*lRIRII_endo kr = 0.0333333333333333
RI => RI_endo ki*RI ki = 0.3333333333333
RI_endo => RI kr*RI_endo kr = 0.0333333333333333
Curator's comment:
(added: 01 May 2007, 21:56:32, updated: 01 May 2007, 21:56:32)
Simulation result corresponds to Fig 5A of the paper. Plot generated by MathSBML.