Saa2016 - Mammalian methionine cycle - approximate bayesian computation Lab

{
  "io": {
    "inputs": [
      {
        "name": "initial_methionine_cycle_state_1",
        "units": "native SBML value",
        "default": 50,
        "maps_to": "metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model.initial_methionine_cycle_state_1",
        "description": "Initial condition for methionine cycle state 1. Maps to bundled SBML symbol `MET`. Applied before the Tellurium simulation starts; this does not change kinetic parameters or equations. Default from bundled SBML initial value."
      },
      {
        "name": "initial_methionine_cycle_state_2",
        "units": "native SBML value",
        "default": 60,
        "maps_to": "metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model.initial_methionine_cycle_state_2",
        "description": "Initial condition for methionine cycle state 2. Maps to bundled SBML symbol `ADOMET`. Applied before the Tellurium simulation starts; this does not change kinetic parameters or equations. Default from bundled SBML initial value."
      },
      {
        "name": "initial_methionine_cycle_state_3",
        "units": "native SBML value",
        "default": 35,
        "maps_to": "metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model.initial_methionine_cycle_state_3",
        "description": "Initial condition for methionine cycle state 3. Maps to bundled SBML symbol `ADOHCY`. Applied before the Tellurium simulation starts; this does not change kinetic parameters or equations. Default from bundled SBML initial value."
      },
      {
        "name": "initial_methionine_cycle_state_4",
        "units": "native SBML value",
        "default": 1.7,
        "maps_to": "metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model.initial_methionine_cycle_state_4",
        "description": "Initial condition for methionine cycle state 4. Maps to bundled SBML symbol `MTHF`. Applied before the Tellurium simulation starts; this does not change kinetic parameters or equations. Default from bundled SBML initial value."
      },
      {
        "name": "initial_methionine_cycle_state_5",
        "units": "native SBML value",
        "default": 3.5,
        "maps_to": "metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model.initial_methionine_cycle_state_5",
        "description": "Initial condition for methionine cycle state 5. Maps to bundled SBML symbol `HCY`. Applied before the Tellurium simulation starts; this does not change kinetic parameters or equations. Default from bundled SBML initial value."
      }
    ],
    "outputs": [
      {
        "name": "methionine_cycle_state_1",
        "maps_to": "metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model.methionine_cycle_state_1"
      },
      {
        "name": "methionine_cycle_state_2",
        "maps_to": "metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model.methionine_cycle_state_2"
      },
      {
        "name": "methionine_cycle_state_3",
        "maps_to": "metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model.methionine_cycle_state_3"
      },
      {
        "name": "methionine_cycle_state_4",
        "maps_to": "metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model.methionine_cycle_state_4"
      },
      {
        "name": "methionine_cycle_state_5",
        "maps_to": "metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model.methionine_cycle_state_5"
      },
      {
        "name": "observable_values",
        "maps_to": "metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model.observable_values"
      },
      {
        "name": "run_summary",
        "maps_to": "metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model.run_summary"
      },
      {
        "name": "observable_labels",
        "maps_to": "metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model.observable_labels"
      }
    ]
  },
  "title": "Saa2016 - Mammalian methionine cycle - approximate bayesian computation Lab",
  "models": [
    {
      "path": "owned/models/metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model",
      "alias": "metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model",
      "parameters": {
        "model_path": "data/MODEL1603150000.xml",
        "integration_step": 0.1
      },
      "provenance": {
        "owned_path": "owned/models/metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model"
      }
    },
    {
      "path": "owned/models/visualisation",
      "alias": "visualisation",
      "provenance": {
        "owned_path": "owned/models/visualisation"
      }
    }
  ],
  "wiring": [
    {
      "to": [
        "visualisation.metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model_observable_values"
      ],
      "from": "metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model.observable_values"
    },
    {
      "to": [
        "visualisation.metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model_run_summary"
      ],
      "from": "metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model.run_summary"
    },
    {
      "to": [
        "visualisation.metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model_observable_labels"
      ],
      "from": "metabolism_sbml_saa2016_mammalian_methionine_cycle_approximate_b_model1603150000_model.observable_labels"
    }
  ],
  "runtime": {
    "duration": 10,
    "initial_inputs": {},
    "communication_step": 1
  },
  "description": "Construction of feasible and accurate kinetic models of metabolism: A Bayesian approachPedro A. It can be used to explore metabolic flux dynamics and compare pathway behavior across conditions.",
  "schema_version": "2.0"
}