Kronik2010 - Predicting Outcomes of Prostate Cancer Immunotherapyby Personalized Mathematical Models Lab
About lab
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.
Runtime
Duration10
Comms Step1
Runs
Total0
Completed0
Failed0
Metadata
Packagekronik2010-predicting-outcomes-of-prostate-cancer-immunotherapyb
Created2026-05-16
Updated2026-05-16
biomodels_ebicurateddrug-responsefaithfulimmunologyimmunotherapymicroenvironmentoncologypharmacologyphysiologysbmlsignal-transductionsignalingsystemsbiologytumor-growthvisualisation
Manifest
{
"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": "owned/models/oncology_sbml_kronik2010_predicting_outcomes_of_prostate_cance_model2001130003_model",
"alias": "oncology_sbml_kronik2010_predicting_outcomes_of_prostate_cance_model2001130003_model",
"provenance": {
"owned_path": "owned/models/oncology_sbml_kronik2010_predicting_outcomes_of_prostate_cance_model2001130003_model"
}
},
{
"path": "owned/models/visualisation",
"alias": "visualisation",
"provenance": {
"owned_path": "owned/models/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"
}
],
"runtime": {
"duration": 10,
"initial_inputs": {},
"communication_step": 1
},
"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"
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