Kronik2010 - Predicting Outcomes of Prostate Cancer Immunotherapyby Personalized Mathematical Models Lab

{
  "io": {
    "inputs": [
      {
        "name": "initial_tumor_volume",
        "label": "Tumor Volume",
        "units": "native SBML value",
        "default": 1000000,
        "maps_to": "oncology_sbml_kronik2010_predicting_outcomes_of_prostate_cance_model2001130003_model.initial_tumor_volume",
        "description": "Initial Tumor Volume. Sets the initial value of bundled SBML symbol `V`."
      }
    ],
    "outputs": [
      {
        "name": "tumor_volume",
        "maps_to": "oncology_sbml_kronik2010_predicting_outcomes_of_prostate_cance_model2001130003_model.tumor_volume",
        "description": "Tumor Volume observable. Maps to SBML symbol `V`."
      },
      {
        "name": "state",
        "maps_to": "oncology_sbml_kronik2010_predicting_outcomes_of_prostate_cance_model2001130003_model.state",
        "description": "Full raw SBML observable record for reproducibility and downstream visualisation."
      },
      {
        "name": "summary",
        "maps_to": "oncology_sbml_kronik2010_predicting_outcomes_of_prostate_cance_model2001130003_model.summary",
        "description": "Change and peak summary across the simulated SBML observables."
      },
      {
        "name": "species_labels",
        "maps_to": "oncology_sbml_kronik2010_predicting_outcomes_of_prostate_cance_model2001130003_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",
    "signal-transduction",
    "signaling",
    "systemsbiology",
    "tumor-growth"
  ],
  "title": "Kronik2010 - Predicting Outcomes of Prostate Cancer Immunotherapyby Personalized Mathematical Models Lab",
  "models": [
    {
      "path": "models/core",
      "alias": "oncology_sbml_kronik2010_predicting_outcomes_of_prostate_cance_model2001130003_model"
    },
    {
      "path": "models/visualisation",
      "alias": "visualisation"
    }
  ],
  "wiring": [
    {
      "to": [
        "visualisation.oncology_sbml_kronik2010_predicting_outcomes_of_prostate_cance_model2001130003_model_state"
      ],
      "from": "oncology_sbml_kronik2010_predicting_outcomes_of_prostate_cance_model2001130003_model.state"
    },
    {
      "to": [
        "visualisation.oncology_sbml_kronik2010_predicting_outcomes_of_prostate_cance_model2001130003_model_summary"
      ],
      "from": "oncology_sbml_kronik2010_predicting_outcomes_of_prostate_cance_model2001130003_model.summary"
    },
    {
      "to": [
        "visualisation.oncology_sbml_kronik2010_predicting_outcomes_of_prostate_cance_model2001130003_model_species_labels"
      ],
      "from": "oncology_sbml_kronik2010_predicting_outcomes_of_prostate_cance_model2001130003_model.species_labels"
    }
  ],
  "package": "kronik2010-predicting-outcomes-of-prostate-cancer-immun-b8457f48",
  "runtime": {
    "duration": 10,
    "initial_inputs": {},
    "communication_step": 1
  },
  "version": "1.0.0",
  "description": "Predicting Outcomes of Prostate Cancer Immunotherapyby Personalized Mathematical ModelsNatalie Kronik1¤, Yuri Kogan1, Moran Elishmereni1, Karin Halevi-Tobias1, Stanimir Vuk-Pavlovic ́2.,Zvia Agur1*.1I. It can be used to explore tumor-related dynamics and compare treatment-response behavior across conditions.",
  "schema_version": "2.0"
}