BioModelsapplication/xmlhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000163?filename=curation_notes.txthttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000163?filename=BIOMD0000000163.pdfhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000163?filename=BIOMD0000000163-biopax3.owlhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000163?filename=BIOMD0000000163-biopax2.owlhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000163?filename=manifest.xmlhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000163?filename=BIOMD0000000163_url.xmlhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000163?filename=metadata.rdfhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000163?filename=BIOMD0000000163-octave.mhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000163?filename=BIOMD0000000163-matlab.mhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000163?filename=BIOMD0000000163.mhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000163?filename=BIOMD0000000163.pnghttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000163?filename=curation_image.jpeghttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000163?filename=BIOMD0000000163.odehttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000163?filename=BIOMD0000000163.vcmlhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000163?filename=BIOMD0000000163_url.sedmlhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000163?filename=BIOMD0000000163.sciprimary200OKZhike ZiManually curatedordinary differential equation modelL2V1https://www.ebi.ac.uk/biomodels/BIOMD000000016317895977falseBioModelsSBMLModelsZi2007 TGFbeta signaling2007MODEL3388742457Zhike Zi, Edda KlippZhike Zi17895977, <h4>Background</h4>Investigation of dynamics and regulation of the TGF-beta signaling pathway is central to the understanding of complex cellular processes such as growth, apoptosis, and differentiation. In this study, we aim at using systems biology approach to provide dynamic analysis on this pathway.<h4>Methodology/principal findings</h4>We proposed a constraint-based modeling method to build a comprehensive mathematical model for the Smad dependent TGF-beta signaling pathway by fitting the experimental data and incorporating the qualitative constraints from the experimental analysis. The performance of the model generated by constraint-based modeling method is significantly improved compared to the model obtained by only fitting the quantitative data. The model agrees well with the experimental analysis of TGF-beta pathway, such as the time course of nuclear phosphorylated Smad, the subcellular location of Smad and signal response of Smad phosphorylation to different doses of TGF-beta.<h4>Conclusions/significance</h4>The simulation results indicate that the signal response to TGF-beta is regulated by the balance between clathrin dependent endocytosis and non-clathrin mediated endocytosis. This model is useful to be built upon as new precise experimental data are emerging. The constraint-based modeling method can also be applied to quantitative modeling of other signaling pathways.. 9, 2. Computational Systems Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany.zhike_zi@molgen.mpg.deMax Planck Institute for Molecular GeneticsBIOMD0000000163<h4>Background</h4>Investigation of dynamics and regulation of the TGF-beta signaling pathway is central to the understanding of complex cellular processes such as growth, apoptosis, and differentiation. In this study, we aim at using systems biology approach to provide dynamic analysis on this pathway.<h4>Methodology/principal findings</h4>We proposed a constraint-based modeling method to build a comprehensive mathematical model for the Smad dependent TGF-beta signaling pathway by fitting the experimental data and incorporating the qualitative constraints from the experimental analysis. The performance of the model generated by constraint-based modeling method is significantly improved compared to the model obtained by only fitting the quantitative data. The model agrees well with the experimental analysis of TGF-beta pathway, such as the time course of nuclear phosphorylated Smad, the subcellular location of Smad and signal response of Smad phosphorylation to different doses of TGF-beta.<h4>Conclusions/significance</h4>The simulation results indicate that the signal response to TGF-beta is regulated by the balance between clathrin dependent endocytosis and non-clathrin mediated endocytosis. This model is useful to be built upon as new precise experimental data are emerging. The constraint-based modeling method can also be applied to quantitative modeling of other signaling pathways.Constraint-based modeling and kinetic analysis of the Smad dependent TGF-beta signaling pathway.Zi Zhike Z, Klipp Edda EHSN1E, determination, Theoretical Model, postnatal development, Significant, AtrII, Act-r, growth and development, Obtained By, Biochemical Pathway, nonselective vesicle endocytosis, apg, DPP-C, phosphorylation, Dose, Social Controls, Long Term, Mathematical Models, TGFbeta, Milk, Milk Growth Factor, Hin-d, Milk Growth, Readability, Techniques, DmelCG9885, Doses, Compared, Extrinsic Pathway Apoptoses, Method, Statistical Significance, responsivity, P-mad, DmelCG7904, Cell Type, symptoms, Generation, dose, Newari, Smad, Effect, Formal Social Controls, placement, DOSE, Dm-DPP, ced, Theoretical Study, Biology, tgf-beta, M(2)23AB, statistically significant, IMPROVED, Provide, P-Mad, Pathways, Comparison, procedures, tgfb, Based, Social, dMAD, dMad, Novel, Intrinsic Pathway Apoptosis, Methodological Studies, Classic, p-Mad, Classical Apoptosis, Mathematical Models and Simulations, atrII, Usefulness, Better, CXXC finger protein 9, Long-Term Effects, Comprehensive, Atr, single organism signaling, TGF-beta Signaling Pathway KEGG, Dependent Dressing, screening, Constraint, Apply, Pathway, anatomical protrusion, Caspase-Dependent Apoptosis, Difference, Dosage, Punt, TGF-beta, Longterm Effect, Tg, Limitation, CG9885, Metabolic Network, Procedure, Course, CG7904, Significance, results, Experimental, signaling (initiator) caspase activity, Atr88CD, induction of apoptosis, Intrinsic Pathway, significant, Atr-II, Non, Extrinsic Pathway Apoptosis, l(2)22Fa, Theoretical Studies, PUNT, Normal Cell, molecular pathway., Cellular, Not, relational spatial quality, Conflict, l(3)10460, Caspase-Dependent, Regulated, l(2)k17036, shv, statistical significance, ADCADN, PMad, UNQ203/PRO229, growth pattern, non-developmental growth, Modeling, DNA (cytosine-5-)-methyltransferase 1, COURSE, Platelet Transforming Growth Factor, Control, En(vvl), signs, Methodological, Controls, Improved, Methodological Study, pSmad, CG12399, Theoretical Models, experimental procedures, Intrinsic Pathway Apoptoses, Dependent for Toilet Use, Dose Level, induction of apoptosis by p53, spine, Cells, Base, Put, Extrinsic Pathway, pMAD, pMad, Nepal Bhasa, Dose per Administration, Regulation, Classical, location, Apoptoses, Mathematical Model, Provided, Contingent, Regulations, Restricted, Non-, simulation, ho, pun, Procedures, Conditional, experimental, Cellular Differentiation, Experimental Models, Effects, Contingency, M(2)LS1, Different, caspase-dependent programmed cell death, number, TGF-beta5, {Cells}, Caspase Dependent Apoptosis, Bone-Derived Transforming Growth Factor, Endocytoses, fastening fasteners) with help, Cell Differentiation, Compare, presence, dependent, Theoretical, protrusion, Bone Derived Transforming Growth Factor, tgfbeta, Cellularity Measurement, Aim, method, AIM, Cellularity, New Lesion, 2/23, Dressing (includes tying shoes, It improved, method used in an experiment, Differentiated, Studies, MAD, Experimental Model, Growth Factor, tgfb5, Type I, Useful, Models, Mediator, Technique, Performance, Application, Mat, study, cell differentiation, DNMT1, Quantitative Constraint, reactivity, Negation, Dpp, DPP, {Course}, methods, Supply, Bathes with Help, DNMT1_HUMAN, Longterm, cell, dlhC, experimental section, mad, BETTER/IMPROVED/RECOVERING, Long-Term, Theoretic, course, apoptosis activator activity, E(zen)2, blk, Study, API6, Cellularity Index, BMP, l(2)k00237, Percent Cellularity, Supplied, Newar Language, CELLULAR, Mathematical, Classic Apoptosis, Statistically Significant, Smad1, Long-Term Effect, dose_level, Model, Differentiation, Principal, Apoptosis, DNA MTase HsaI, DNA (cytosine-5)-methyltransferase 1, New, NEW, Cellularity Grade, l(3)j5A5, Computer Modeling, findings, Tgf-r, Protocol Treatment Course, TGF-b, plasma membrane invagination, Formal Social Control, Dependent, DNMT, Phosphorylations, {Dose}, Model (Theoretical), Build, Factor, MCMT, lap, Cell, Conditionality, development, count in organism, Social Control, Programmed Cell Death, DNA methyltransferase HsaI, Applied, Systems, chemical analysis, Long Term Effects, Bathing self with help, Nuclear, background, techniques, Approach, CXXC9, Basic, New Lesion Identification, differentiation, transforming growth factor beta, apoptosis, CT-2, Pre-Release Version, l(2)10638, postnatal growth, Cell Differentiation Process, Basis, TRTDOS, dose level, Understanding, Collector, Negated, CXXC-type zinc finger protein 9, Dresses with Help, introduction, TGF-beta signaling pathway, Longterm Effects, Collected By, Classic Apoptoses, plan specification, No, l(2)K00237, Generated, Models (Theoretical), Differential, Mediated, DmelCG12399, c28, signalling process, TGF-B, Dependent Bathing, Cell Types, commitment to apoptosis, Restriction, regulation, Simulation, assay, dpd1, response, STK-C, growth, CLEC2C, m.HsaI, methodologyextent, Sectors, SMAD family member 2, ho, Public Sectors, smad-2, YB, Effects, MADR2, M(2)LS1, AUTSX5, TGF-beta5, number, ted, Bone-Derived Transforming Growth Factor, tmp, Copyrights, NOVH, DPP-C, CCN3, 2210402P09Rik, QM, Long Term, Protoplasm, TGFbeta, Milk, Bone Derived Transforming Growth Factor, tgfbeta, Milk Growth Factor, CED, Hin-d, Milk Growth, DmelCG9885, Yb, horsetail nucleus, Figs, SMAD 2, CG2262, Growth Factor, tgfb5, Public Enterprise, Effect, Enterprises, CG2706, fs(1)M104, DSmad2, PIST, Dm-DPP, hSMAD2, MADH2, DmelCG7615, ced, Dpp, DPP, TGFB, tgf-beta, Longterm, M(2)23AB, Smad-2, JV18-1, Public Domains, JV18, smad2, AI844555, Long-Term, IGFBP9, tgfb, Madr2, Public Enterprises, DEPP, SMAD2, Rubberplants, blk, IBP-9, Kiaa4053, BMP, MAD homolog 2, Rubberplant, L10, Mothers against DPP homolog 2, Fseg, Smad2, Long-Term Effect, NOVh, Enterprise, LAP, Long-Term Effects, 7120426M23Rik, DmelCG2262, Decidual protein induced by progesterone, Papers, TGF-b, completeness, Cytoplasms, DmelCG2706, Madh2, Longterm Effect, TGF-beta, Tg, DXS648, CG9885, Factor, lap, presence., Fasting-induced gene protein, count in organism, IGFBP-9, dSMAD2, Public, Public Domain, l(2)22Fa, Long Term Effects, l(1)G0348, DSMAD2, CAL, Domains, XSmad2, cell nucleus, NOV, Sad, dSmad2, PlexA1, GOPC1, Domain, Data Base, hMAD-2, l(2)k17036, shv, Plxn1, mMad2, Mad-related protein 2, l(2)10638, Platelet Transforming Growth Factor, nov, nucleus of neuraxis, sad, DPD1, mKIAA4053, dsmad2, fs(1)Y[b], Longterm Effects, dJ94G16.2, SMOX, FIG, Fig, Sector, C130088N23Rik, Protoplasms, EG:95B7.8, CG7615, 2600013D04Rik, PLXN1, smox, dpd1, DXS648EDependent Dressing, TGF-beta Signaling Pathway KEGG, Constraint, Restricted, determination, Conditional, Dependent, Contingency, Limitation, fastening fasteners) with help, apg, Conditionality, dependent, 2/23, Dressing (includes tying shoes, chemical analysis, P-mad, Bathing self with help, MAD, Smad, Basic, Mat, Quantitative Constraint, PMad, Bathes with Help, Modeling, P-Mad, Basis, mad, En(vvl), Based, pSmad, CG12399, Dresses with Help, E(zen)2, Dependent for Toilet Use, dMAD, dMad, l(2)K00237, TGF-beta signaling pathway., l(2)k00237, DmelCG12399, c28, p-Mad, Base, Dependent Bathing, Smad1, Restriction, pMAD, pMad, assay, ContingentfalseZi2007_TGFbeta_signaling The model reproduces the time profiles of Total Smad2 in the nucleus as well as the cytoplasm as depicted in 2D and also the other time profiles as depicted in Fig 2. Two parameters that are not present in the paper are introduced here for illustration purposes and they are Total Smad2n and Total Smad2c. The term kr_EE*LRC_EE has not been included in the ODE's for T1R_surf, T2R_surf and TGFbeta in the paper but is included in this model. MathSBML was used to reproduce the simulation result. 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. 2024-08-212024-09-022008-02-25BIOMD0000000163hsa0435017895977MODEL3388742457BIOMD0000000163GO:0017015GO:0005576GO:0005634GO:0005737GO:0007184GO:0006886GO:0032905GO:0002090GO:0031623GO:0032906GO:0005160GO:0030163131567Q15796Q13485Q8NER5P37173P01137