Models
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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
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
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
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 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
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Not specified
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
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
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
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