dePillis2013 - Mathematical modeling of regulatory T cell effects on renal cell carcinoma treatment Lab

{
  "io": {
    "inputs": [
      {
        "name": "initial_tumor_cells",
        "label": "Tumor Cells",
        "units": "native SBML value",
        "default": 4662000000,
        "maps_to": "oncology_sbml_depillis2013_mathematical_modeling_of_regulatory_biomd0000000908_model.initial_tumor_cells",
        "description": "Initial Tumor Cells. Sets the initial value of bundled SBML symbol `T`."
      },
      {
        "name": "drug_treatment_level",
        "label": "Drug Treatment Level",
        "units": "native SBML value",
        "default": 0.00000947552761007735,
        "maps_to": "oncology_sbml_depillis2013_mathematical_modeling_of_regulatory_biomd0000000908_model.drug_treatment_level",
        "description": "Drug Treatment Level. Overrides bundled SBML parameter `D`."
      }
    ],
    "outputs": [
      {
        "name": "tumor_cells",
        "maps_to": "oncology_sbml_depillis2013_mathematical_modeling_of_regulatory_biomd0000000908_model.tumor_cells",
        "description": "Tumor Cells observable. Maps to SBML symbol `T`."
      },
      {
        "name": "state",
        "maps_to": "oncology_sbml_depillis2013_mathematical_modeling_of_regulatory_biomd0000000908_model.state",
        "description": "Full raw SBML observable record for reproducibility and downstream visualisation."
      },
      {
        "name": "summary",
        "maps_to": "oncology_sbml_depillis2013_mathematical_modeling_of_regulatory_biomd0000000908_model.summary",
        "description": "Change and peak summary across the simulated SBML observables."
      },
      {
        "name": "species_labels",
        "maps_to": "oncology_sbml_depillis2013_mathematical_modeling_of_regulatory_biomd0000000908_model.species_labels",
        "description": "Mapping from selected raw SBML observable symbols to display labels."
      }
    ]
  },
  "tags": [
    "biomodels_ebi",
    "curated",
    "drug-response",
    "faithful",
    "immunology",
    "immunotherapy",
    "microenvironment",
    "oncology",
    "pharmacology",
    "physiology",
    "sbml",
    "systemsbiology",
    "tumor-growth"
  ],
  "title": "dePillis2013 - Mathematical modeling of regulatory T cell effects on renal cell carcinoma treatment Lab",
  "models": [
    {
      "path": "models/core",
      "alias": "oncology_sbml_depillis2013_mathematical_modeling_of_regulatory_biomd0000000908_model"
    },
    {
      "path": "models/visualisation",
      "alias": "visualisation"
    }
  ],
  "wiring": [
    {
      "to": [
        "visualisation.oncology_sbml_depillis2013_mathematical_modeling_of_regulatory_biomd0000000908_model_state"
      ],
      "from": "oncology_sbml_depillis2013_mathematical_modeling_of_regulatory_biomd0000000908_model.state"
    },
    {
      "to": [
        "visualisation.oncology_sbml_depillis2013_mathematical_modeling_of_regulatory_biomd0000000908_model_summary"
      ],
      "from": "oncology_sbml_depillis2013_mathematical_modeling_of_regulatory_biomd0000000908_model.summary"
    },
    {
      "to": [
        "visualisation.oncology_sbml_depillis2013_mathematical_modeling_of_regulatory_biomd0000000908_model_species_labels"
      ],
      "from": "oncology_sbml_depillis2013_mathematical_modeling_of_regulatory_biomd0000000908_model.species_labels"
    }
  ],
  "package": "depillis2013-mathematical-modeling-of-regulatory-t-cell-477d4093",
  "runtime": {
    "duration": 10,
    "initial_inputs": {},
    "communication_step": 1
  },
  "version": "1.0.0",
  "description": "Mathematical modeling of regulatory T cell effects on renal cell carcinoma treatmentLisette dePillis 1, , Trevor Caldwell 2, , Elizabeth Sarapata 2, and Heather Williams 2,1. It can be used to explore tumor-related dynamics and compare treatment-response behavior across conditions.",
  "schema_version": "2.0"
}