Models
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Copasi file chronic inflammation Abulikemu et al 2020 (altered units TNF and MMP8); see supplemntal material: TNF and MMP7 concentration upgrade of the models All computations for the present paper were completed by using the model prepared and tested in Abulikemu et al 2018. Then, little attention was paid to the unit in which concentrations were expressed, except for the concentration of fibroblasts, which we found important for modelling the effect of confluency. This led to a predicted TNF ...
Creators: Hans V. Westerhoff, Abulikemu Abudukelimu and Matteo Barberis
Submitter: Hans V. Westerhoff
Model type: Ordinary differential equations (ODE)
Model format: Copasi
Environment: Copasi
Copasi file chronic inflammation Abulikemu et al 2020 (altered units TNF and MMP8); see supplemntal material: TNF and MMP7 concentration upgrade of the models All computations for the present paper were completed by using the model prepared and tested in Abulikemu et al 2018. Then, little attention was paid to the unit in which concentrations were expressed, except for the concentration of fibroblasts, which we found important for modelling the effect of confluency. This led to a predicted TNF ...
Creators: Hans V. Westerhoff, Ablikim Abulikemu, Matteo Barberis
Submitter: Hans V. Westerhoff
Model type: Ordinary differential equations (ODE)
Model format: Copasi
Environment: Copasi
This is a model about a ROS network that exhibits five design principles, and has been calibrated so as to predict quantitatively various steady state concentrations. 10191125.
Instructions RUN the model for steady state. For the Menadione experiment set the initial concentration of 'Menadione' species to experimental dosing i.e. 100 000 nM (0.1 mM) and make the simulation type "reaction" for both the species i.e. 'Menadione' and 'Menadione_internal'. Then run for 24 hr i.e. 1500 minutes approx. ...
Creators: Hans V. Westerhoff, Raju Prasad Sharma, Alexey Kolodkin
Submitter: Hans V. Westerhoff
Model type: Ordinary differential equations (ODE)
Model format: Copasi
Environment: Copasi
Model that can be used to obtain the figures of Abudulikemu et al 2018: Abudukelimu, A., Barberis, M., Redegeld, F.A., Sahin, N., and Westerhoff, H.V. (2018). Predictable Irreversible Switching Between Acute and Chronic Inflammation. Front Immunol 9, 1596.
Creators: Hans V. Westerhoff, Ablikim Abudukelimu
Submitter: Hans V. Westerhoff
Model type: Ordinary differential equations (ODE)
Model format: Copasi
Environment: Copasi
(Abudulikemu et al 2000 (also 2018) Standard model of acute mode Figure 32.
Creators: Hans V. Westerhoff, Ablikim Abudukelimu
Submitter: Hans V. Westerhoff
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
Particularly figure 2 of of Abudulikemu et al 2020 in press
Creator: Hans V. Westerhoff
Submitter: Hans V. Westerhoff
Model type: Ordinary differential equations (ODE)
Model format: Copasi
Environment: Copasi
BPG stability notebook
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Mathematica
PGK model for S. solfataricus
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Algebraic equations
Model format: Mathematica
Environment: Mathematica
Here is a kinetic model (in COPASI format) of L. lactis glycolysis.
Creator: Mark Musters
Submitter: Mark Musters
Model type: Ordinary differential equations (ODE)
Model format: Copasi
Environment: Copasi
PGK-GAPDH model Sulfolobus kouril8
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
PGK-GAPDH model yeast kouril7
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
PGK-GAPDH models yeast and Sulfolobus Fig. 4 in manuscript
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Mathematica
PGK 70C SBML
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
PGK yeast Fig1a
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Mathematica
PGK yeast with/without recycling
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
SBML description of L. lactis glycolysis. Same as the uploaded Copasi file
Creator: Mark Musters
Submitter: Mark Musters
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Not specified
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Not specified
Model format: Not specified
Environment: Not specified
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Not specified
Model format: SBML
Environment: JWS Online
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Not specified
Model format: SBML
Environment: JWS Online
Creator: Malgorzata Adamczyk
Submitter: Malgorzata Adamczyk
Model type: Not specified
Model format: SBML
Environment: Not specified
Preliminary metabolic network of S. pyogenes including primary metabolism, polysaccharide metabolism, purine and pyrimidine biosoynthesis, teichoic acid biosynthesis, fatty acid and phospholipid bioynthesis, amino acid metabolism, vitamins and cofactors. The model still needs to be validated.
Creator: Jennifer Levering
Submitter: Jennifer Levering
Model type: Metabolic network
Model format: SBML
Environment: Not specified
Creator: Nadine Veith
Submitter: Nadine Veith
Model type: Partial differential equations (PDE)
Model format: SBML
Environment: Not specified
Batch and chemostat model of L lactis. Scope of the model is to provide a mechanistic explanation of the switch between mixed acid and homolactic fermentation.
Creator: domenico bellomo
Submitter: domenico bellomo
Model type: Partial differential equations (PDE)
Model format: Matlab package
Environment: Matlab
The principles of Stealthy Engineering (Adamczyk et al.: Biotechnology Journal 2012; 7(7):877-83) are illustrated in this model by emulating a cross engineering intervention between L. lactis and S. cerevisiae.
The case study consists of replacing the native glucose uptake system of L. lactis with that native to the yeast S. cerevisiae. A modified version of Hoefnagel et al.’s model of L. lacrtis’ central metabolism was used as starting point. The total functional replacement of the PTS with the ...
Creators: Malgorzata Adamczyk, Hans V. Westerhoff, Ettore Murabito
Submitter: Ettore Murabito
Model type: Ordinary differential equations (ODE)
Model format: Copasi
Environment: Copasi
A reconstruction of the cellular metabolism of the opportunistic human pathogen Enterococcus faecalis V583 represented as stoichiometric model and analysed using constraint-based modelling approaches
Creators: Nadine Veith, Margrete Solheim, Koen van Grinsven, Jennifer Levering, Jeroen Hugenholtz, Helge Holo, Ingolf Nes, Bas Teusink, Ursula Kummer, Brett G Olivier, Ruth Grosseholz
Submitter: Nadine Veith
Model type: Linear equations
Model format: SBML
Environment: Not specified
Mechanistical model of the catalytic cycle of Trypanothione Synthetase
Creators: Jurgen Haanstra, Alejandro Leroux
Submitter: Jurgen Haanstra
Model type: Linear equations
Model format: Copasi
Environment: Copasi
An ODE model of the gene regulation network governing sporulation initiation in Bacillus subtilis to be run in Matlab.
The network incorporates four sporulation-related signals: nutrient supply, DNA damage, the products of the competence genes and the bacterial population size.
Run execute_bacillus_sporulation_initiation.m to simulate the model. This file also contains the signal-related parameters which can be altered to investigate the effect of competing signals.
Some results for this model ...
Creator: Sara Jabbari
Submitter: Sara Jabbari
Model type: Ordinary differential equations (ODE)
Model format: Matlab package
Environment: Not specified
Here, we use hyperbolic tangents to fit experimental data of AB fermentation in C. acetobutylicum in continous culture at steady state for different external pHs. The estimated parameters are used to define acidogenic and solventogenic phase. Furthermore, an transition phase is identified which cannot be assigned to acidogenesis or solventogenesis.
Several plots compare the fits to the experimental data.
Creator: Thomas Millat
Submitter: Thomas Millat
Model type: Not specified
Model format: Matlab package
Environment: Matlab
This function estimates the parameters of growth functions of the acid-forming and solvent-forming population observed in 'forward'-shift experiments of phosphate-limited continuous cultures of C. acetobutylicum. The parameters are used in the 'Two-Populations'-Model of the pH-induced metabolic shift.
It assumed that the found behaviour of the optical density during these experiments results from a phenotypic switch caused by the changing pH level.
Creator: Thomas Millat
Submitter: Thomas Millat
Model type: Not specified
Model format: Matlab package
Environment: Matlab
3D structure prediction of LDH enzymes from four LAB by comparative modeling against x-ray structure of LDH from B. stearothermophilis (template, PDB ID: 1LDN). The computation was performed with a protocol that uses "automodel.very_fast" settings of Modeller program (http://salilab.org/modeller/).
Creator: Anna Feldman-Salit
Submitter: Anna Feldman-Salit
Model type: Not specified
Model format: Not specified
Environment: Not specified
Comparison of electrostatic potentials within the allosteric binding sites of LDH enzymes to estimate the binding affinity of the FBP molecule is performed with the PIPSA program. The program uses the structure of enzymes in the PDB format and computed electrostatic potentials in the GRD format.
Creator: Anna Feldman-Salit
Submitter: Anna Feldman-Salit
Model type: Not specified
Model format: Not specified
Environment: Not specified
Computation is performed for the modeled 3D structures of LDH enzymes (in PDB format) with the UHBD program, for pH 6 and pH 7.
Creator: Anna Feldman-Salit
Submitter: Anna Feldman-Salit
Model type: Not specified
Model format: Not specified
Environment: Not specified
Binding energies of phosphate ions to the allosteric and catalytic sites were estimated with a program GRID (http://www.moldiscovery.com/soft_grid.php). The calculations were performed for the modeled LDH structures from four LABs, at pH 6 and 7, in presence and absence of the FBP molecule. The phosphate ion was presented as a probe.
Creator: Anna Feldman-Salit
Submitter: Anna Feldman-Salit
Model type: Not specified
Model format: Not specified
Environment: Not specified
In order to estimate whether Pi has an activatory or an inhibitory effect on the enzymes, the computed probe binding energies (from GRID results, Part 4) were compared with those for the LDH from L. plantarum whose activity is known to be unaffected by Pi.
The binding energies of the Pi probe in the allosteric binding site (AS) and the COO probe in the catalytic binding site (CS) of LDH from L. plantarum were defined as E¬AS,threshold and ECS,threshold, respectively. For the other LDH enzymes, ...
Creator: Anna Feldman-Salit
Submitter: Anna Feldman-Salit
Model type: Algebraic equations
Model format: Not specified
Environment: Not specified
The zip file contains two executable Matlab functions.
File named 'fnct_gen_tfcompmod.m' generates a Simbiology model based on the following interactions: R + X <-> RX -> R + X + Px R + Y <-> RY -> R + Y + Py R + Z <-> RZ -> R + Z + Pz Y + Pz -> Pz Px -> Py -> Pz ->
We assume much higher reaction speeds of sigma factor RNApol binding/unbinding compared to protein expression. Protein expression can therefore be represented by Michaelis-Menten like kinetic ...
Creator: Ulf Liebal
Submitter: Ulf Liebal
Model type: Ordinary differential equations (ODE)
Model format: Matlab package
Environment: Matlab
The model describes the catabolism of Escherichia coli and its regulation. The metabolic reactions are modeled by the thermokinetic model formalism. The model is simplified by assuming rapid equilibrium of many reactions. Regulation is modeled by phenomenological laws describing the activation or repression of enzymes and genes in dependence of metabolic signals. The model is intended to describe the behavior of E. coli in a chemostat culture in depedence on the oxygen supply.
The model is described ...
Creators: Michael Ederer, David Knies
Submitter: Michael Ederer
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Not specified
Structural models of the LAB PYKs of L. lactis, L. plantarum, S. pyogenes and E. faecalis including the "best" docking solutions of potential allosteric ligands. The structures were derived by homology modeling based on the template of E. coli and B. stearothermophilus. PYK models and ligands are provided as .pdb files and can be displayed by using the program PyMOL, for instance.
Creators: Nadine Veith, Anna Feldman-Salit, Stefan Henrich, Rebecca Wade
Submitter: Nadine Veith
Model type: Not specified
Model format: Not specified
Environment: Not specified
Model of reconstituted gluconeogenesis system in S. solfataricus based on the individual kinetic models for PGK, GAPDH, TPI, FBPAase.
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
Exponential decay model of gluconeogenic intermediates
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Not specified
Mathematical model for TPI kinetics, GAP and DHAP saturation, and inhibition with 3PG and PEP.
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Not specified
Mathematical model for GAPDH kinetics, BPG, NADPH, NADP, GAP and Pi saturation.
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Not specified
Mathematical model for FBPAase kinetics, saturation with DHAP and GAP
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Not specified
Mathematical model for PGK kinetics, ADP, ATP, 3PG and BPG saturation.
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Not specified
SBML models without activity of the glycolytic enzymes in the cytosol:
Glycolysis_noActivityInCytosol_1a.xml Model 1a Glycolysis_noActivityInCytosol_1b.xml Model 1b Glycolysis_noActivityInCytosol_2.xml Model 2 Glycolysis_noActivityInCytosol_3.xml Model 3 Glycolysis_noActivityInCytosol_4.xml Model 4 Glycolysis_noActivityInCytosol_5.xml Model 5 Glycolysis_noActivityInCytosol_6.xml Model 6
SBML models with activity of the glycolytic enzymes in the cytosol:
Glycolysis_withActivityInCytosol_1a.xm Model ...
Creator: Fiona Achcar
Submitter: Fiona Achcar
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Not specified
This ordinary-differential equation model is a spatially lumped model showing the behaviour of oxygen in the three compartments medium, membrane and cytoplasm and its impact on FNR inactivation, hereby showing the effects of different oxygen concentrations, diffusion coefficients and reaction rates. The model was created with the Matlab SimBiology toolbox.
Creator: Samantha Nolan
Submitter: David Knies
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Not specified
This partial-differential equations model focuses on the oxygen gradients in consideration of the three-dimensional cell and environment.
Creator: Samantha Nolan
Submitter: David Knies
Model type: Partial differential equations (PDE)
Model format: Mathematica
Environment: Not specified
Code for joint probabilistic inference of transcription factor behaviour and gene-transcription factor as well as metabolite-transcription factor interaction based on genome and metabolite data.
Creators: Botond Cseke, Guido Sanguinetti
Submitter: Botond Cseke
Model type: Not specified
Model format: Matlab package
Environment: Matlab
The model presents the response of E.coli to different levels of oxygen supply, in which the oxidases, Cyo and Cyd, and their regulators, FNR and ArcBA systems, are included. The initial file 0.xml and supporting documents are for the model with FNR only. Four 0.xml files provided are at AAU level 31, 85, 115 and 217 respectively. The ArcBA system can be activated by revising the number of agents, ArcB, ArcA dimer, ArcA monomer, ArcA tetramer and ArcA octamer, in the initial file. The model needs ...
only lacZ synthesis reduced by inhibitor in BSA115
Creator: Ulf Liebal
Submitter: Ulf Liebal
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
The model file represents the expression of beta-gal from a sigB dependent promoter after sigb production was stimulated by IPTG. The model is based on an assumption that a hypothetical protein degrates the sigb factor.
Creator: Ulf Liebal
Submitter: Ulf Liebal
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
This is a JWS model of the successful model for data representation. It realises regulation by a hypothetical sigB dependent protein that degrades beta-Gal.
Creator: Ulf Liebal
Submitter: Ulf Liebal
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
The model represents a hypothetical situation in which an anti-sigmafactor reduces sigB efficacy.
Creator: Ulf Liebal
Submitter: Ulf Liebal
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
The zip folder contains files that allow simulation of stressosome dynamics. The models are based on a cellular automaton approach. Each protein of RsbR and RsbS is located in the crystal structure of the stressosome. The proteins can be phosphorylated or not and these states determine the future of neighbouring proteins. To simulate the model open the file 'liebal_stressosome-model_12_workflow-matlab.m' in Matlab. It is written in the cell-model, put the cursor into a cell that you wish to ...
Creator: Ulf Liebal
Submitter: Ulf Liebal
Model type: Agent based modelling
Model format: Matlab package
Environment: Matlab
Bayesian model for inference of the activity of transcription factors from targets' mRNA levels. A standalone C sharp package (runs on linux and mac under MONO).
Creator: Guido Sanguinetti
Submitter: Guido Sanguinetti
Model type: Not specified
Model format: Not specified
Environment: Not specified
This model assumes a phenotypic switch between an acid- and solvent-forming population caused by the changing pH levels. The two phenotypes differ in their transcriptomic, proteomic, and ,thus, their metabolomic profile. Because the growth rates of these phenotypes depends on the extracellular pH, the initiation of the pH-shift results in a significant decline of the acidogenic population. Simultaneously, the solvent-forming population rises and establishes an new steady state.
The model is build ...
Creators: Thomas Millat, Graeme Thorn, Olaf Wolkenhauer, John King
Submitter: Thomas Millat
Model type: Ordinary differential equations (ODE)
Model format: Matlab package
Environment: Matlab
The fitted function describes the pH-drop during 'forward'-shift experiments and the increase of the pH during 'reverse'-shift experiments. The estimated parameters are used to compute the changing pH level in the models of the pH.induced metabolic shift in continuous cultures under phosphate limitation of C. acetobutylicum. Furthermore, the parameters can be applied to join different independent experiments into a single data set.
To fit the changing pH level, an exponential function and a ...
Creator: Thomas Millat
Submitter: Thomas Millat
Model type: Not specified
Model format: Matlab package
Environment: Matlab
First darft of a model including glycolysis and the transcription and translation of the enzymes. See the datafile "Information on the darft transcription/translation model." for information.
Creator: Fiona Achcar
Submitter: Fiona Achcar
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Not specified
Using optical tweezers to position yeast cells in a microfluidic chamber, we were able to observe sustained oscillations in individual isolated cells. Using a detailed kinetic model for the cellular reactions, we simulated the heterogeneity in the response of the individual cells, assuming small differences in a single internal parameter. By operating at two different flow rates per experiment, we observe four of categories of cell behaviour. The present model (gustavsson4) predicts the steady-state ...
Creators: Franco du Preez, Jacky Snoep, Dawie van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
The model includes glycolysis, pentosephosphate pathway, purine salvage reactions, purine de novo synthesis, redox balance and biomass growth. The network balances adenylate pool as opened moiety.
Creator: Maksim Zakhartsev
Submitter: Maksim Zakhartsev
Model type: Metabolic network
Model format: SBML
Environment: Copasi
Using optical tweezers to position yeast cells in a microfluidic chamber, we were able to observe sustained oscillations in individual isolated cells. Using a detailed kinetic model for the cellular reactions, we simulated the heterogeneity in the response of the individual cells, assuming small differences in a single internal parameter. By operating at two different flow rates per experiment, we observe four of categories of cell behaviour. The present model (gustavsson1) predicts the limit ...
Creators: Franco du Preez, Jacky Snoep, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
Using optical tweezers to position yeast cells in a microfluidic chamber, we were able to observe sustained oscillations in individual isolated cells. Using a detailed kinetic model for the cellular reactions, we simulated the heterogeneity in the response of the individual cells, assuming small differences in a single internal parameter. By operating at two different flow rates per experiment, we observe four of categories of cell behaviour. The present model (gustavsson2) predicts the damped ...
Creators: Franco du Preez, Jacky Snoep, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
Using optical tweezers to position yeast cells in a microfluidic chamber, we were able to observe sustained oscillations in individual isolated cells. Using a detailed kinetic model for the cellular reactions, we simulated the heterogeneity in the response of the individual cells, assuming small differences in a single internal parameter. By operating at two different flow rates per experiment, we observe four of categories of cell behaviour. The present model (gustavsson3) predicts the steady-state ...
Creators: Franco du Preez, Jacky Snoep, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An existing detailed kinetic model for the steady-state behavior of yeast glycolysis was tested for its ability to simulate dynamic behavior. This model (dupreez1) is the basis kinetic model derived from that published by Teusink et al., 2000 (PMID: 10951190).
Creators: Franco du Preez, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An existing detailed kinetic model for the steady-state behavior of yeast glycolysis was tested for its ability to simulate dynamic behavior. This model (dupreez2) is an oscillating version of the basis kinetic model (dupreez1) derived from that published by Teusink et al., 2000 (PMID: 10951190).
Creators: Franco du Preez, Jacky Snoep, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An existing detailed kinetic model for the steady-state behavior of yeast glycolysis was tested for its ability to simulate dynamic behavior. This model (dupreez3) is an oscillating version of the model published by Teusink et al., 2000 (PMID: 10951190), which describes data for glycolytic intermediates in oscillating yeast cultures reported by Richard et al., 1996 (PMID: 8813760).
Creators: Franco du Preez, Jacky Snoep, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An existing detailed kinetic model for the steady-state behavior of yeast glycolysis was tested for its ability to simulate dynamic behavior. This model (dupreez4) is an oscillating version of the model published by Teusink et al., 2000 (PMID: 10951190), which describes data for glycolytic intermediates in oscillating yeast cultures reported by Richard et al., 1996a (PMID: 8813760) as well as the rapid synchronization following the mixing of two yeast cultures that oscillate 180 degrees out of ...
Creators: Franco du Preez, Jacky Snoep, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An existing detailed kinetic model for the steady-state behavior of yeast glycolysis was tested for its ability to simulate dynamic behavior. This model (dupreez5) is an oscillating version of the model published by Teusink et al., 2000 (PMID: 10951190), which describes the amplitude bifurcation of oscillating yeast cultures in a CSTR setup reported by Hynne et al., 2001 (PMID: 11744196).
Creators: Franco du Preez, Jacky Snoep, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An existing detailed kinetic model for the steady-state behavior of yeast glycolysis was tested for its ability to simulate dynamic behavior. This model (dupreez6) is an oscillating version of the model published by Teusink et al., 2000 (PMID: 10951190), which describes data for glycolytic intermediates in cell free extracts of oscillating yeast cultures reported by Das and Busse, 1991 (PMCID: 1260073).
Creators: Franco du Preez, Jacky Snoep, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An existing detailed kinetic model for the steady-state behavior of yeast glycolysis was tested for its ability to simulate dynamic behavior. This model (dupreez7) is an oscillating version of the model published by Teusink et al., 2000 (PMID: 10951190), which describes the fluorescence signal of NADH in oscillating yeast cultures reported by Nielsen et al., 1998 (PMID: 17029704).
Creators: Franco du Preez, Jacky Snoep, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
The zip file contains model files and an experiment file. Unpack it in a directory and navigate with matlab to there. Use the 'matlab_execution_guide.m' for simulation and visualisation of the model. This file is written in matlab cell mode, so it is not a stand alone function.
Three models have been developed to test their capacity to reproduce the experimental data from Study: 'Controlled sigmaB induction in shake flask' with Assay: 'IPTG induction of sigmaB in BSA115'. One model assumes a ...
Creator: Ulf Liebal
Submitter: Ulf Liebal
Model type: Ordinary differential equations (ODE)
Model format: Matlab package
Environment: Matlab
input: array of investigated quenching temperatures and volumetric flows output: quenching time and coil length as function of quenching temperature, and quenching time as function of temperature for varying coil lengths
Creator: Sebastian Curth
Submitter: Sebastian Curth
Model type: Algebraic equations
Model format: Matlab package
Environment: Matlab
The kinetic model includes sugar uptake, degradation of glucose into pyruvate and the fermentation of pyruvate.
Creator: Jennifer Levering
Submitter: Jennifer Levering
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
The kinetic model includes sugar uptake, degradation of glucose into pyruvate and the fermentation of pyruvate.
Creators: Jennifer Levering, Mark Musters
Submitter: Jennifer Levering
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
The zip-folder contains files for execution in matlab that allow for the simulation of stressosome dynamics and reproduction of published data on the stressosome. The important file for execution is 'liebal_stressosome-model_12_workflow-matlab.m'.
Creator: Ulf Liebal
Submitter: Ulf Liebal
Model type: Agent based modelling
Model format: Matlab package
Environment: Matlab
Quorum sensing(QS) allows the bacteria to monitor their surroundings and the size of their population. Staphylococcus aureus makes use of QS to regulate the production of virulence factors. This mathematical model of the QS system in S aureus was presented and analyzed (Journal of Mathematical Biology(2010) 61:17–54) in order to clarify the roles of the distinct interactions that make up the QS process, demonstrating which reactions dominate the behaviour of the system at various timepoints. ...
Creators: Sara Jabbari, John King, Adrian Koerber, Paul Williams
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An ODE model representing the metabolic network governing acid and solvent production by Clostridium acetobutylicum (Haus et al. BMC Systems Biology 2011, 5:10), incorporating the effect of pH upon gene regulation and subsequent end-product levels. This model describes the third of four experiments in which the pH of the culture was shifted. For this experiment acidogenesis at pH 5.7 was maintained for 121 hours, after which the pH control was stopped, allowing the natural metabolic shift to the ...
Creators: Sara Jabbari, Sylvia Haus
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An ODE model representing the metabolic network governing acid and solvent production by Clostridium acetobutylicum (Haus et al. BMC Systems Biology 2011, 5:10), incorporating the effect of pH upon gene regulation and subsequent end-product levels. This model describes the last of four experiments in which the pH of the culture was shifted. For this experiment the pH shift was reversed compared to the first three (shift from pH 4.5 to 5.7), with the pH control switched off after 129 hours. ...
Creators: Sara Jabbari, Sylvia Haus
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An ODE model representing the metabolic network governing acid and solvent production by Clostridium acetobutylicum (Haus et al. BMC Systems Biology 2011, 5:10), incorporating the effect of pH upon gene regulation and subsequent end-product levels. This model describes the second of four experiments in which the pH of the culture was shifted. For this experiment acidogenesis at pH 5.7 was maintained for 137.5 hours, after which the pH control was stopped, allowing the natural metabolic shift to ...
Creators: Sara Jabbari, Sylvia Haus
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An ODE model representing the metabolic network governing acid and solvent production by Clostridium acetobutylicum (Haus et al. BMC Systems Biology 2011, 5:10), incorporating the effect of pH upon gene regulation and subsequent end-product levels. This model describes the first of four experiments in which the pH of the culture was shifted. For this experiment acidogenesis at pH 5.7 was maintained for 137 hours, after which the pH control was stopped, allowing the natural metabolic shift to the ...
Creators: Sara Jabbari, Sylvia Haus
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
Bacillus subtilis cells may opt to forgo normal cell division and instead form spores if subjected to certain environmental stimuli, for example nutrient deficiency or extreme temperature. The gene regulation net-work governing sporulation initiation accordingly incorporates a variety of signals and is of significant complexity. The present model (Bulletin of Mathematical Biology (2011) 73:181–211) includes four of these signals: nutrient levels, DNA damage, the products of the competence genes, ...
Creators: Sara Jabbari, John Heap, John King
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
Fixed parameter model, where the glycolysis model of bloodstream form T. brucei is extended with the pentose phosphate pathway and a ribokinase in the glycosome. Non-final version.
Creators: Eduard Kerkhoven, Fiona Achcar
Submitter: Eduard Kerkhoven
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Copasi
Fixed parameter model, where the glycolysis model of bloodstream form T. brucei is extended with the pentose phosphate pathway and an ATP:ADP antiporter over the glycosomal membrane. Non-final version.
Creators: Eduard Kerkhoven, Fiona Achcar
Submitter: Eduard Kerkhoven
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
SBML file supplementary material of the publication.
Creators: Fiona Achcar, Barbara Bakker, Mike Barrett, Rainer Breitling, Eduard Kerkhoven
Submitter: Fiona Achcar
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Not specified
The model describes the electron transport chain (ETC) of Escherichia coli by ordinary differential equations. Also a simplified growth model based on an abstract reducing potential describing the balance of electron donor (glucose) and electron acceptors is coupled to the ETC. The model should reproduce and predict the regulation of the described system for different oxygen availability within the aerobiosis scale (glucose limited continuous culture<=>chemostat). Therefore oxygen is changed ...
Creator: Sebastian Henkel
Submitter: Sebastian Henkel
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
A model of E. coli central carbon core metabolism, used as starting point for B. subtilis modelling. It is developed by Chassagnole et al. doi:10.1002/bit.10288.
Creators: Ulf Liebal, Fei He
Submitter: Ulf Liebal
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Not specified
Simplified model of the electron-transport chain(s) (ETC) of Escherichia coli and its regulation by ArcA and FNR. The goal is to demonstrate a hypothetical design principle in the regulatory structure (->partly qualitative parameter values). Oxygen is changed slowly (100% aerobiosis at 1000000 time units) thus the basis variable is not the time but the oxygen flux voxi.
Creator: Sebastian Henkel
Submitter: Sebastian Henkel
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Not specified
An ODE model representing the metabolic network governing acid and solvent production by Clostridium acetobutylicum, incorporating the effect of pH upon gene regulation and subsequent end-product levels.
The zip file containes 4 models (in SBML), each representing slightly different experimental conditions.
Creators: Sara Jabbari, Sylvia Haus
Submitter: The JERM Harvester
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Not specified
Creators: Jay Moore, David Hodgson, Veronica Armendarez, Emma Laing , Govind Chandra, Mervyn Bibb
Submitter: Jay Moore
Model type: Metabolic network
Model format: BioPAX
Environment: Not specified
Creator: Paul Heusden
Submitter: The JERM Harvester
Model type: Not specified
Model format: Not specified
Environment: Not specified
The model can simulate the the dynamics of sigB dependent transcription at the transition to starvation. It is was developed along the comic in 'sigB-activation-comic_vol1'. Parameters were partly taken from Delumeau et al., 2002, J. Bact. and Igoshin et al., 2007, JMB. Parameter estimation was performed using experimental data from '0804_shake-flask'. Use the .m-file with matlab as: % reading initial conditions from the file: inic = sigb_model_liebal;
% performing the simulation: [t,y] = ...
Creator: Ulf Liebal
Submitter: Ulf Liebal
Model type: Ordinary differential equations (ODE)
Model format: Matlab package
Environment: Matlab
The model describes the Entner-Doudoroff pathway in Sulfolobus solfataricus under temperature variation. The package contains source code written in FORTRAN as well as binaries for Mac OSX, Linux, and Windows. If compiling from source code, a FORTRAN compiler is required. On-line versions of the model are also available at: http://bioinfo.ux.uis.no/sulfosys http://jjj.biochem.sun.ac.za/sysmo/projects/Sulfo-Sys/index.html
Creator: Peter Ruoff
Submitter: Peter Ruoff
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: Not specified
The agent-based model involves the representation of each individual molecule of interest as an autonomous agent that exists within the cellular environment and interacts with other molecules according to the biochemical situation. FLAME environmet has beem used for agent-based development. The FLAME framework is an enabling tool to create agent-based models that can be run on high performance computers (HPCs). Models are created based upon extended finite state machines that include message input ...
Creator: Afsaneh Maleki-Dizaji
Submitter: Afsaneh Maleki-Dizaji
Model type: Agent based modelling
Model format: Not specified
Environment: FLAME