Larbat2016.1 - Modeling the diversion of primary carbon flux into secondary metabolism under variable nitrate and light or dark conditions (Base Model) Lab
About lab
This is a global mathematical model describing metabolic partitioning of carbon resources in plants between growth and defense, as a function of nitrate fertilization. It can be used to explore metabolic flux dynamics and compare pathway behavior across conditions.
Runtime
Duration10
Comms Step1
Runs
Total0
Completed0
Failed0
Metadata
Packagelarbat2016-1-modeling-the-diversion-of-primary-carbon-flux-into
Created2026-05-15
Updated2026-05-15
biomodels_ebifaithfulmetabolismodesbmltelluriumvisualisation
Manifest
{
"io": {
"inputs": [
{
"name": "initial_metabolic_pathway_state_1",
"units": "native SBML value",
"default": 0.7,
"maps_to": "metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model.initial_metabolic_pathway_state_1",
"description": "Initial condition for metabolic pathway state 1. Maps to bundled SBML symbol `sucr`. Applied before the Tellurium simulation starts; this does not change kinetic parameters or equations. Default from bundled SBML initial value."
},
{
"name": "initial_metabolic_pathway_state_2",
"units": "native SBML value",
"default": 8.06,
"maps_to": "metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model.initial_metabolic_pathway_state_2",
"description": "Initial condition for metabolic pathway state 2. Maps to bundled SBML symbol `EtrioseP`. Applied before the Tellurium simulation starts; this does not change kinetic parameters or equations. Default from bundled SBML initial value."
},
{
"name": "initial_metabolic_pathway_state_3",
"units": "native SBML value",
"default": 0.00001,
"maps_to": "metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model.initial_metabolic_pathway_state_3",
"description": "Initial condition for metabolic pathway state 3. Maps to bundled SBML symbol `Ephe`. Applied before the Tellurium simulation starts; this does not change kinetic parameters or equations. Default from bundled SBML initial value."
},
{
"name": "initial_metabolic_pathway_state_4",
"units": "native SBML value",
"default": 5,
"maps_to": "metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model.initial_metabolic_pathway_state_4",
"description": "Initial condition for metabolic pathway state 4. Maps to bundled SBML symbol `N`. Applied before the Tellurium simulation starts; this does not change kinetic parameters or equations. Default from bundled SBML initial value."
},
{
"name": "initial_metabolic_pathway_state_5",
"units": "native SBML value",
"default": 0,
"maps_to": "metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model.initial_metabolic_pathway_state_5",
"description": "Initial condition for metabolic pathway state 5. Maps to bundled SBML symbol `starch`. Applied before the Tellurium simulation starts; this does not change kinetic parameters or equations. Default from bundled SBML initial value."
}
],
"outputs": [
{
"name": "metabolic_pathway_state_1",
"maps_to": "metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model.metabolic_pathway_state_1"
},
{
"name": "metabolic_pathway_state_2",
"maps_to": "metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model.metabolic_pathway_state_2"
},
{
"name": "metabolic_pathway_state_3",
"maps_to": "metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model.metabolic_pathway_state_3"
},
{
"name": "metabolic_pathway_state_4",
"maps_to": "metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model.metabolic_pathway_state_4"
},
{
"name": "metabolic_pathway_state_5",
"maps_to": "metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model.metabolic_pathway_state_5"
},
{
"name": "observable_values",
"maps_to": "metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model.observable_values"
},
{
"name": "run_summary",
"maps_to": "metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model.run_summary"
},
{
"name": "observable_labels",
"maps_to": "metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model.observable_labels"
}
]
},
"title": "Larbat2016.1 - Modeling the diversion of primary carbon flux into secondary metabolism under variable nitrate and light or dark conditions (Base Model) Lab",
"models": [
{
"path": "owned/models/metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model",
"alias": "metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model",
"parameters": {
"model_path": "data/BIOMD0000000857.xml",
"integration_step": 0.1
},
"provenance": {
"owned_path": "owned/models/metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model"
}
},
{
"path": "owned/models/visualisation",
"alias": "visualisation",
"provenance": {
"owned_path": "owned/models/visualisation"
}
}
],
"wiring": [
{
"to": [
"visualisation.metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model_observable_values"
],
"from": "metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model.observable_values"
},
{
"to": [
"visualisation.metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model_run_summary"
],
"from": "metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model.run_summary"
},
{
"to": [
"visualisation.metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model_observable_labels"
],
"from": "metabolism_sbml_larbat2016_1_modeling_the_diversion_of_primary_c_biomd0000000857_model.observable_labels"
}
],
"runtime": {
"duration": 10,
"initial_inputs": {},
"communication_step": 1
},
"description": "This is a global mathematical model describing metabolic partitioning of carbon resources in plants between growth and defense, as a function of nitrate fertilization. It can be used to explore metabolic flux dynamics and compare pathway behavior across conditions.",
"schema_version": "2.0"
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