# Models

What is a Model?**400**Models visible to you, out of a total of

**642**

Mathematica notebook for the parameterisation of the PK rate equation based on the experimental SEEK data set

**Creators: **Dawie van Niekerk, Jacky Snoep

**Submitter**: Dawie van Niekerk

**Model type**: Ordinary differential equations (ODE)

**Model format**: Mathematica

**Environment**: Not specified

Mathematica notebook for the parameterisation of the PGM rate equation based on SEEK linked experimental data.

**Creators: **Dawie van Niekerk, Jacky Snoep

**Submitter**: Dawie van Niekerk

**Model type**: Ordinary differential equations (ODE)

**Model format**: Mathematica

**Environment**: Not specified

Mathematical model for HK kinetics, GLC and ATP saturation, and inhibition with G6P and ADP.

**Creators: **Dawie van Niekerk, Jacky Snoep

**Submitter**: Dawie van Niekerk

**Model type**: Ordinary differential equations (ODE)

**Model format**: Mathematica

**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