Dataset Information

Vilar2006_TGFbeta

ABSTRACT: 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.

SUBMITTER: Katja Wegner

PROVIDER: BIOMD0000000101 | BioModels | 2024-09-02

REPOSITORIES: BioModels

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Dataset's files

Source:

			Action	DRS
	BIOMD0000000101?filename=BIOMD0000000101-biopax2.owl	Owl
	BIOMD0000000101?filename=BIOMD0000000101-biopax3.owl	Owl
	BIOMD0000000101?filename=BIOMD0000000101-matlab.m	Other
	BIOMD0000000101?filename=BIOMD0000000101-octave.m	Other
	BIOMD0000000101?filename=BIOMD0000000101.m	Other

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Publications

Signal processing in the TGF-beta superfamily ligand-receptor network.

Vilar Jose M G JM Jansen Ronald R Sander Chris C

PLoS computational biology 20060127 1

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 ligan ...[more]

PMID: 16446785

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Project description:Similar to the bone marrow, the mammary gland contains a distinct population of Hoechst-effluxing side population cells, MG-SPs. To better characterize MG-SPs, their microarray gene profiles were compared to the remaining cells, which retain Hoechst dye (MG-NSPs). For analysis, gene ontology (GO) that describes genes in terms of biological processes and ontology traverser (OT) that performs enrichment analysis were utilized. OT showed that MG-SP specific genes were enriched in the GO categories of cell cycle regulation and checkpoints, multi-drug resistant transporters, organogenesis, and vasculogenesis. The MG-NSP upregulated genes were enriched in the GO category of cellular organization and biogenesis which includes basal epithelial markers, p63, smooth muscle actin (SMA), myosin, alpha-6 integrin, cytokeratin (CK) 14, as well as luminal markers, CK8 and CD24. Additional studies showed that a higher percentage of MG-SPs exist in the G1 phase of the cell cycle compared to the MG-NSPs. G1 cell cycle block of MG-SPs may be explained by higher expression of cell cycle negative regulatory genes such as TGF-beta2 (transforming growth factor-beta2), IGFBP-5 (insulin like growth factor binding protein-5), P18 INK4C and Wnt-5a (wingless-5a). Accordingly, a smaller percentage of MG-SPs expressed nuclear b-catenin, possibly as a consequence of the higher expression of Wnt-5a. In conclusion, microarray gene profiling suggests that MG-SPs are a lineage deficient mammary gland sub-population expressing key genes involved in cell cycle regulation, development and angiogenesis. Supplemental File Descriptions: Table 1 is a list of 1632 Genes differentially expressed by MG-SP and MG-NSP; Criteria for comparison included 1.2-fold difference in expression levels, false discovery rate (FDR) 9.4%, P value less than 0.05. Table 2 is a list of 771 Genes differentially expressed by MG-SP and MG-NSP; Criteria for comparison included 1.5-fold difference in expression levels, FDR 3.4%, P value less than 0.05. Table 3 is a list of 335 Genes differentially expressed by MG-SP and MG-NSP; Criteria for comparison included 2-fold difference in expression levels, FDR 0%, P value less than 0.05. Table 4 is a list of 90 Genes differentially expressed by MG-SP and MG-NSP; Criteria for comparison included 2-fold difference in expression levels, FDR 0%, P value less than 0.01. Keywords: Normal C57BL/6 Mammary Gland Epithelial Cells