Lavigne2021 - Non-spatial model of viral infection dynamics and interferon response of well-mixed viral infection Lab

About lab

Lavigne2021 - Non-spatial model of viral infection dynamics and interferon response of well-mixed viral infection Lab

Curated immunology lab using the bundled source model as the scientific source of truth.

What You'll See

This captured run documents the default Lavigne2021 - Non-spatial model of viral infection dynamics and interferon response of well-mixed viral infection configuration for 10.0 time units with a 1.0 communication step. Default inputs include Initial Infected Cells Antiviral, Initial Infected Cells, Initial Interferon, and Initial Target Cells. Reported outputs include infected_cells_antiviral, infected_cells, interferon, and target_cells. The screenshots below pair the run-interpretation table with Pathogen and immune response and Largest state excursions so the README shows both trajectories and the strongest state changes from the same dark-mode run.

Output Visualizations

The run-interpretation table summarizes the configured Lavigne2021 - Non-spatial model of viral infection dynamics and interferon response of well-mixed viral infection simulation and its final-state diagnostics.

Lavigne2021 - Non-spatial model of viral infection dynamics and interferon response of well-mixed viral infection Lab - run interpretation

The Pathogen and immune response time series follows the selected immune, pathogen, tumor, or signaling quantities across the simulated horizon.

Pathogen and immune response

The largest state excursions chart ranks the state variables that moved furthest during the run.

Largest state excursions

This ordinary differential equation model is described in the following article:'Autocrine and paracrine interferon signalling as ‘ring vaccination’ and ‘contact tracing’ strategies to suppress virus. It can be used to explore immune response dynamics and compare pathway-level behavior across conditions.

Runtime

Duration10

Comms Step1

Runs

Total0

Completed0

Failed0

Metadata

Packagelavigne2021-non-spatial-model-of-viral-infection-dynamics-and-in

Created2026-05-15

Updated2026-05-15

immunologysbmlbiomodels_ebifaithfulcuratedvisualisation

Manifest

{
  "io": {
    "inputs": [
      {
        "name": "initial_infected_cells_antiviral",
        "label": "Initial Infected Cells Antiviral",
        "units": "native source value",
        "default": 0,
        "maps_to": "immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model.initial_infected_cells_antiviral",
        "description": "Initial Infected Cells Antiviral. Sets the initial value of bundled SBML species `Infected_cells_antiviral`."
      },
      {
        "name": "initial_infected_cells",
        "label": "Initial Infected Cells",
        "units": "native source value",
        "default": 0,
        "maps_to": "immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model.initial_infected_cells",
        "description": "Initial Infected Cells. Sets the initial value of bundled SBML species `Infected_cells`."
      },
      {
        "name": "initial_interferon",
        "label": "Initial Interferon",
        "units": "native source value",
        "default": 0,
        "maps_to": "immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model.initial_interferon",
        "description": "Initial Interferon. Sets the initial value of bundled SBML species `IFN`."
      },
      {
        "name": "initial_target_cells",
        "label": "Initial Target Cells",
        "units": "native source value",
        "default": 400000000,
        "maps_to": "immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model.initial_target_cells",
        "description": "Initial Target Cells. Sets the initial value of bundled SBML species `Target_cells`."
      },
      {
        "name": "initial_refractory_cells",
        "label": "Initial Refractory Cells",
        "units": "native source value",
        "default": 0,
        "maps_to": "immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model.initial_refractory_cells",
        "description": "Initial Refractory Cells. Sets the initial value of bundled SBML species `Refractory_cells`."
      }
    ],
    "outputs": [
      {
        "name": "infected_cells_antiviral",
        "maps_to": "immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model.infected_cells_antiviral"
      },
      {
        "name": "infected_cells",
        "maps_to": "immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model.infected_cells"
      },
      {
        "name": "interferon",
        "maps_to": "immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model.interferon"
      },
      {
        "name": "target_cells",
        "maps_to": "immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model.target_cells"
      },
      {
        "name": "refractory_cells",
        "maps_to": "immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model.refractory_cells"
      },
      {
        "name": "state",
        "maps_to": "immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model.state"
      },
      {
        "name": "summary",
        "maps_to": "immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model.summary"
      },
      {
        "name": "species_labels",
        "maps_to": "immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model.species_labels"
      }
    ]
  },
  "title": "Lavigne2021 - Non-spatial model of viral infection dynamics and interferon response of well-mixed viral infection Lab",
  "models": [
    {
      "path": "owned/models/immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model",
      "alias": "immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model",
      "provenance": {
        "owned_path": "owned/models/immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model"
      }
    },
    {
      "path": "owned/models/visualisation",
      "alias": "visualisation",
      "provenance": {
        "owned_path": "owned/models/visualisation"
      }
    }
  ],
  "wiring": [
    {
      "to": [
        "visualisation.immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model_state"
      ],
      "from": "immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model.state"
    },
    {
      "to": [
        "visualisation.immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model_summary"
      ],
      "from": "immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model.summary"
    },
    {
      "to": [
        "visualisation.immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model_species_labels"
      ],
      "from": "immunology_sbml_lavigne2021_non_spatial_model_of_viral_infection_biomd0000001021_model.species_labels"
    }
  ],
  "runtime": {
    "duration": 10,
    "initial_inputs": {},
    "communication_step": 1
  },
  "description": "This ordinary differential equation model is described in the following article:'Autocrine and paracrine interferon signalling as ‘ring vaccination’ and ‘contact tracing’ strategies to suppress virus. It can be used to explore immune response dynamics and compare pathway-level behavior across conditions.",
  "schema_version": "2.0"
}

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