Giani2019 - Computational modeling to predict MAP3K8 effects as mediator of resistance to vemurafenib in thyroid cancer stem cells Lab

{
  "io": {
    "inputs": [
      {
        "name": "initial_free_egfr",
        "label": "Free EGFR",
        "units": "native SBML value",
        "default": 10,
        "maps_to": "oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model.initial_free_egfr",
        "description": "Initial Free EGFR. Sets the initial value of bundled SBML symbol `species_1`."
      },
      {
        "name": "initial_sos_inactive",
        "label": "Sos Inactive",
        "units": "native SBML value",
        "default": 10,
        "maps_to": "oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model.initial_sos_inactive",
        "description": "Initial Sos Inactive. Sets the initial value of bundled SBML symbol `species_3`."
      },
      {
        "name": "initial_ras_inactive",
        "label": "Ras Inactive",
        "units": "native SBML value",
        "default": 10,
        "maps_to": "oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model.initial_ras_inactive",
        "description": "Initial Ras Inactive. Sets the initial value of bundled SBML symbol `species_5`."
      },
      {
        "name": "initial_raf1_inactive",
        "label": "Raf1 Inactive",
        "units": "native SBML value",
        "default": 10,
        "maps_to": "oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model.initial_raf1_inactive",
        "description": "Initial Raf1 Inactive. Sets the initial value of bundled SBML symbol `species_7`."
      },
      {
        "name": "initial_mek_inactive",
        "label": "Mek Inactive",
        "units": "native SBML value",
        "default": 10,
        "maps_to": "oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model.initial_mek_inactive",
        "description": "Initial Mek Inactive. Sets the initial value of bundled SBML symbol `species_9`."
      },
      {
        "name": "initial_erk",
        "label": "ERK",
        "units": "native SBML value",
        "default": 10,
        "maps_to": "oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model.initial_erk",
        "description": "Initial ERK. Sets the initial value of bundled SBML symbol `species_11`."
      }
    ],
    "outputs": [
      {
        "name": "free_egfr",
        "maps_to": "oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model.free_egfr",
        "description": "Free EGFR observable. Maps to SBML symbol `species_1`."
      },
      {
        "name": "sos_inactive",
        "maps_to": "oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model.sos_inactive",
        "description": "Sos Inactive observable. Maps to SBML symbol `species_3`."
      },
      {
        "name": "ras_inactive",
        "maps_to": "oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model.ras_inactive",
        "description": "Ras Inactive observable. Maps to SBML symbol `species_5`."
      },
      {
        "name": "raf1_inactive",
        "maps_to": "oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model.raf1_inactive",
        "description": "Raf1 Inactive observable. Maps to SBML symbol `species_7`."
      },
      {
        "name": "mek_inactive",
        "maps_to": "oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model.mek_inactive",
        "description": "Mek Inactive observable. Maps to SBML symbol `species_9`."
      },
      {
        "name": "erk",
        "maps_to": "oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model.erk",
        "description": "ERK observable. Maps to SBML symbol `species_11`."
      },
      {
        "name": "state",
        "maps_to": "oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model.state",
        "description": "Full raw SBML observable record for reproducibility and downstream visualisation."
      },
      {
        "name": "summary",
        "maps_to": "oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model.summary",
        "description": "Change and peak summary across the simulated SBML observables."
      },
      {
        "name": "species_labels",
        "maps_to": "oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model.species_labels",
        "description": "Mapping from selected raw SBML observable symbols to display labels."
      }
    ]
  },
  "tags": [
    "biomodels_ebi",
    "curated",
    "drug-response",
    "faithful",
    "oncology",
    "pharmacology",
    "physiology",
    "sbml",
    "systemsbiology",
    "tumor-growth"
  ],
  "title": "Giani2019 - Computational modeling to predict MAP3K8 effects as mediator of resistance to vemurafenib in thyroid cancer stem cells Lab",
  "models": [
    {
      "path": "models/core",
      "alias": "oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model"
    },
    {
      "path": "models/visualisation",
      "alias": "visualisation"
    }
  ],
  "wiring": [
    {
      "to": [
        "visualisation.oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model_state"
      ],
      "from": "oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model.state"
    },
    {
      "to": [
        "visualisation.oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model_summary"
      ],
      "from": "oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model.summary"
    },
    {
      "to": [
        "visualisation.oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model_species_labels"
      ],
      "from": "oncology_sbml_giani2019_computational_modeling_to_predict_map3_biomd0000000883_model.species_labels"
    }
  ],
  "package": "giani2019-computational-modeling-to-predict-map3k8-effe-815b010a",
  "runtime": {
    "duration": 10,
    "initial_inputs": {},
    "communication_step": 1
  },
  "version": "1.0.0",
  "description": "Computational modeling to predict MAP3K8 effects as mediator of resistance to vemurafenib in thyroid cancer stem cells. It can be used to explore tumor-related dynamics and compare treatment-response behavior across conditions.",
  "schema_version": "2.0"
}