Models
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Parameters rescaled and scaling factors set to 1
Creator: Uriel Urquiza Garcia
Submitter: Uriel Urquiza Garcia
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Copasi
DownloadThis is the scaled version of U2020.4 in sbml file. It already contains the scaling factors
Creator: Uriel Urquiza Garcia
Submitter: Uriel Urquiza Garcia
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Copasi
Paramters rescaled and scaling factors set to 1
Creator: Uriel Urquiza Garcia
Submitter: Uriel Urquiza Garcia
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: Not specified
Paramteres rescaled and scaling factors set to 1
Creator: Uriel Urquiza Garcia
Submitter: Uriel Urquiza Garcia
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Copasi
Parameters rescaled and scaling factors set to 1
Creator: Uriel Urquiza Garcia
Submitter: Uriel Urquiza Garcia
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: Not specified
Derived from U2019.3 from Testing the inferred rate of dynamic, gene regulatory network in absolute units
Creators: Uriel Urquiza Garcia, Andrew Millar
Submitter: Uriel Urquiza Garcia
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: Not specified
Sbml version of U2019.4 with reacaling factors values already incoporated in the model. This was generated autmatically using tellurium python package
Creator: Uriel Urquiza Garcia
Submitter: Uriel Urquiza Garcia
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Copasi
This file was derived from U2020.3 by introducing the scalig factors in the required locations in the model. This files is used then for numerically rescaling the model for matching synthetic protein data.
Creator: Uriel Urquiza Garcia
Submitter: Uriel Urquiza Garcia
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: Not specified
We recommend to use a virtual environment with a python 3.11 distribution to reproduce our results. Using anaconda and the environment file eulerpi_env.yml, the working virtual environment is set up through the prompt
conda env create -f eulerpi_env.yml
The environment file eulerpi_env.yml contains a human-readable list of all required dependencies. Consequently, these dependencies can also be installed manually.
In addition to this README and the environment file, the downloaded .zip ...
Creator: Vincent Wagner
Submitter: Vincent Wagner
Model type: Not specified
Model format: Not specified
Environment: Not specified
HSD11B1 inhibition by AZD4017 and the effect on cortisone and 11KA4 metabolism was simulated in Mathematica. Figure 6 of the manuscript is reproduced in the notebook.
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Mathematica
Mathematica notebook for simulation of combined effect of HSD11B1/AKR1C3 ratio variation and HSD11B1 inhibition, surface plots are generated shown in Fig. 4 of the manuscript.
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: Mathematica
HSD11B1 was inhibited by CBX and the effect on cortisone and 11KA4 conversion was simulated. Model simulated in Mathematica, Figure 3 panels are presented.
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Mathematica
Mathematic notebook for enzyme kinetic analysis and model fit, including figure generation for manuscript.
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Not specified
Model format: Mathematica
Environment: Mathematica
Mathematica notebook with model simulation of metabolite profiles after 24h incubation with different ratios of HSD11B1 and AKR1C3 transfected HEK293 cells.
Creator: Jacky Snoep
Submitter: Jacky Snoep
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: Mathematica
Creator: Vincent Wagner
Submitter: Vincent Wagner
Model type: Not specified
Model format: Not specified
Environment: Not specified
First version of Genome-scale metabolic model (GEM) for reconstraction of flavonoids biosynthetic pathways. This model includes as a chassis , the Pseudomonas Putida GEM (iJN1411) . It includes the metabolic reconstruction of more than 500 flavonoids and more than 500 reactions related to the flavonoid biosynthesis.
Creators: David San León Granado, Juan Nogales, Álvaro Gargantilla Becerra
Submitter: David San León Granado
Model type: Metabolic network
Model format: SBML
Environment: Matlab
Creators: Dawie van Niekerk, Jacky Snoep
Submitter: Dawie van Niekerk
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
Creators: Dawie van Niekerk, Jacky Snoep
Submitter: Dawie van Niekerk
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
Creators: Dawie van Niekerk, Jacky Snoep
Submitter: Dawie van Niekerk
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
This folder contains the python code for developing weighted loss trainer (WeLT) with all the expiremnatal work. Here is the link for our public [GitHub repository] (https://github.com/mobashgr/WELT.git).
Creator: Ghadeer Mobasher
Submitter: Ghadeer Mobasher
Model type: Not specified
Model format: Python code
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
Creators: Dawie van Niekerk, Jacky Snoep
Submitter: Dawie van Niekerk
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Mathematica
Creators: Dawie van Niekerk, Jacky Snoep
Submitter: Dawie van Niekerk
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Mathematica
Creators: Dawie van Niekerk, Jacky Snoep
Submitter: Dawie van Niekerk
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Mathematica
Creators: Dawie van Niekerk, Jacky Snoep
Submitter: Dawie van Niekerk
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Mathematica
The FEM models how metabolic slowdown will induce the age-related changes of weight gain, insulin resistance, basal inflammation, mitochondrial dysfunction, as well as the age-related disease of atherosclerosis, via a series of unavoidable homeostatic shifts.
Creators: James Wordsworth, Pernille Yde Nielsen
Submitter: James Wordsworth
Model type: Ordinary differential equations (ODE)
Model format: R package
Environment: Not specified
Creators: Dawie van Niekerk, Jacky Snoep
Submitter: Dawie van Niekerk
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Mathematica
Creators: Dawie van Niekerk, Jacky Snoep
Submitter: Dawie van Niekerk
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Mathematica
Creators: Dawie van Niekerk, Jacky Snoep
Submitter: Dawie van Niekerk
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Not specified
Creators: Dawie van Niekerk, Jacky Snoep
Submitter: Dawie van Niekerk
Model type: Ordinary differential equations (ODE)
Model format: Mathematica
Environment: Mathematica
