Models
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Atlantic salmon (Salmo salar) is the most valuable farmed fish globally and there is much interest in optimizing its genetics and rearing conditions for growth and feed efficiency. Marine feed ingredients must be replaced to meet global demand, with challenges for fish health and sustainability. Metabolic models can address this by connecting genomes to metabolism, which converts nutrients in the feed to energy and biomass, but such models are currently not available for major aquaculture species ...
Creators: Maksim Zakhartsev, Filip Rotnes, Marie Gulla, Ove Oyas, Jesse van Dam, Maria Suarez Diez, Fabian Grammes, Wout van Helvoirt, Jasper Koehorst, Peter Schaap, Yang Jin, Liv Torunn Mydland, Arne Gjuvsland, Sandve Simen, Vitor Martins dos Santos, Jon Olav Vik
Submitter: Jon Olav Vik
Model type: Stoichiometric model
Model format: SBML
Environment: Not specified
Originally submitted model file for PLaSMo accession ID PLM_74, version 1
Creators: BioData SynthSys, Yin Hoon Chew
Submitter: BioData SynthSys
Model type: Ordinary differential equations (ODE)
Model format: Simile XML v3
Environment: Not specified
Simplified model file for PLaSMo accession ID PLM_9, version 1 (use simplified if your software cannot read the file, e.g. Sloppy Cell)
Creators: BioData SynthSys, Andrew Millar, Andrew Millar
Submitter: BioData SynthSys
Model type: Not specified
Model format: SBML
Environment: Not specified
Originally submitted model file for PLaSMo accession ID PLM_9, version 1
Creators: BioData SynthSys, Andrew Millar, Andrew Millar
Submitter: BioData SynthSys
Model type: Not specified
Model format: SBML
Environment: Not specified
Simplified model file for PLaSMo accession ID PLM_9, version 2 (use simplified if your software cannot read the file, e.g. Sloppy Cell)
Creators: BioData SynthSys, Andrew Millar, Andrew Millar
Submitter: BioData SynthSys
Model type: Not specified
Model format: SBML
Environment: Not specified
Originally submitted model file for PLaSMo accession ID PLM_9, version 2
Creators: BioData SynthSys, Andrew Millar, Andrew Millar
Submitter: BioData SynthSys
Model type: Not specified
Model format: SBML
Environment: Not specified
Genome-scale metabolic model (GEM) for Streptomyces albus, maintained on https://github.com/SysBioChalmers/Salb-GEM.
Creator: Cheewin Kittikunapong
Submitter: Cheewin Kittikunapong
Model type: Metabolic network
Model format: SBML
Environment: Matlab
Thrombotic complications and coagulopathy in COVID-19
Creators: Goar Frischmann, Gisela Fobo, Corinna Montrone
Submitter: Marek Ostaszewski
Model type: Graphical model
Model format: SBML
Environment: Not specified
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
Executable versions of selected COVID-19 Disease Map diagrams, in SBML-Qual, converted using CaSQ: https://lifeware.inria.fr/~soliman/post/casq/
Creator: Anna Niarakis
Submitter: Marek Ostaszewski
Model type: Boolean network
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
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
Creator: Vincent Wagner
Submitter: Vincent Wagner
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
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Not specified
Model format: SBML
Environment: JWS Online
This model describes a core process during endocytosis. Intracellular vesicles called early endosomes contain the endocytosed cargo, e.g. signaling components like growth factors and RTKs, pathogens like viruses and nutrients like iron in transferrin. Early endosomes form an interacting pool of thousands of vesicles and jointly constitute the sorting and transport machinery in the endocytic pathway. Together with the cargo, membrane components travel to other compartments of the pathway which ...
Creator: Lutz Brusch
Submitter: Lutz Brusch
Model type: Partial differential equations (PDE)
Model format: SBML
Environment: Not specified
Creators: Dawie van Niekerk, Jacky Snoep
Submitter: Dawie van Niekerk
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Mathematica
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
Creators: Dawie van Niekerk, Jacky Snoep
Submitter: Dawie van Niekerk
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Mathematica
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
Originally submitted model file for PLaSMo accession ID PLM_24, version 1
Creators: BioData SynthSys, Jonathan Massheder
Submitter: BioData SynthSys
Model type: Not specified
Model format: Simile XML v3
Environment: Not specified
Creators: Dawie van Niekerk, Jacky Snoep
Submitter: Dawie van Niekerk
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
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 (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