Tang2019 - Pharmacology modelling of AURKB and ZAK interaction in TNBC Lab

About lab

Tang2019 - Pharmacology modelling of AURKB and ZAK interaction in TNBC

This Biosimulant lab wraps Tang2019 - Pharmacology modelling of AURKB and ZAK interaction in TNBC as a runnable oncology model with a companion visualization module. Aurora Kinase B and ZAK interaction model Equivalent of the stochastic model used in 'Network pharmacology model predicts combined Aurora B and ZAK inhibition in MDA-MB-231 breast cancer cells' by Tan. It can be used to explore treatment-response dynamics and compare scenario outcomes across configurations.

What You'll See

The lab asks: How does the bundled treatment-response model evolve under its baseline source conditions? It runs for 10.0 time units with a communication step of 1.0. The run uses the model defaults declared by the curated SBML wrapper. The generated visualizations focus on ATM, SRC, BAD, PTEN, SHC1, and PKN1, combining trajectory, endpoint-comparison, and summary-table views from one completed dark-mode run.

In this captured run, BAD peaked at 38.348 and BAD moved by 37.350 native units across 10.0 simulation windows.

Output Visualizations

Tang2019 - Pharmacology modelling of AURKB and ZAK interaction in TNBC - run interpretation

Summary table for Tang2019 - Pharmacology modelling of AURKB and ZAK interaction in TNBC, reporting the scientific question, observed answer (largest change: BAD at 37.350 native units), evidence (peak observable: BAD), dominant module, and caveat.

Tang2019 - Pharmacology modelling of AURKB and ZAK interaction in TNBC - timeseries visualization

Trajectories of ATM, SRC, BAD, PTEN, SHC1, and PKN1 across the 10.0 simulation. In this run BAD climbed from 1.000 to 38.348 and SRC fell from 1.000 to 0.4010 — the largest movements among the focused observables.

Tang2019 - Pharmacology modelling of AURKB and ZAK interaction in TNBC - bar visualization

Endpoint ranking of the focused observables. Top 3 by final value: BAD = 38.348, SHC1 = 11.084, PTEN = 4.667, with 3 more observables below.

Model Context

Core model: models/core
Visualization model: models/visualisation
Standard: other
Upstream source: biomodels_ebi:BIOMD0000000940
License: CC0
Visual scope: Drug/treatment response and tumour-state change
Caveat: Values are native SBML quantities; the cleanup does not reinterpret source equations.

Inputs

Input	Maps To	Default	Notes
Kd tgfbr1 source parameter	`oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.kd_tgfbr1_level`	`0.45`	Kd tgfbr1 source parameter. Maps to bundled SBML parameter `kd_tgfbr1`.
K tgfbr1 source parameter	`oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.k_tgfbr1_level`	`0.5`	K tgfbr1 source parameter. Maps to bundled SBML parameter `k_tgfbr1`.
ATM	`oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.initial_atm`	`1.0`	Initial ATM. Sets the initial value of bundled SBML symbol `ATM`.
SRC	`oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.initial_src`	`1.0`	Initial SRC. Sets the initial value of bundled SBML symbol `SRC`.
BAD	`oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.initial_bad`	`1.0`	Initial BAD. Sets the initial value of bundled SBML symbol `BAD`.
PTEN	`oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.initial_pten`	`1.0`	Initial PTEN. Sets the initial value of bundled SBML symbol `PTEN`.

Outputs

Output	Maps To	Role
`atm`	`oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.atm`	ATM observable.
`src`	`oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.src`	SRC observable.
`bad`	`oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.bad`	BAD observable.
`pten`	`oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.pten`	PTEN observable.
`shc1`	`oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.shc1`	SHC1 observable.
`pkn1`	`oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.pkn1`	PKN1 observable.
`state`	`oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.state`	Full raw SBML observable record for reproducibility and downstream visualisation.
`summary`	`oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.summary`	Change and peak summary across the simulated SBML observables.
`species_labels`	`oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.species_labels`	Mapping from selected raw SBML observable symbols to display labels.

Runtime

Duration: 10.0
Communication step: 1.0

Running Locally

biosimulant labs serve .

Aurora Kinase B and ZAK interaction model Equivalent of the stochastic model used in 'Network pharmacology model predicts combined Aurora B and ZAK inhibition in MDA-MB-231 breast cancer cells' by Tan. 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

Packagetang2019-pharmacology-modelling-of-aurkb-and-zak-interaction-in

Created2026-05-16

Updated2026-05-16

biomodels_ebicurateddrug-responsefaithfuloncologypharmacologyphysiologysbmlsystemsbiologytumor-growthvisualisation

Manifest

{
  "io": {
    "inputs": [
      {
        "name": "kd_tgfbr1_source_parameter",
        "label": "Kd tgfbr1 source parameter",
        "units": "native SBML value",
        "default": 0.45,
        "maps_to": "oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.kd_tgfbr1_source_parameter",
        "description": "Kd tgfbr1 source parameter. Maps to bundled SBML parameter `kd_tgfbr1`."
      },
      {
        "name": "k_tgfbr1_source_parameter",
        "label": "K tgfbr1 source parameter",
        "units": "native SBML value",
        "default": 0.5,
        "maps_to": "oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.k_tgfbr1_source_parameter",
        "description": "K tgfbr1 source parameter. Maps to bundled SBML parameter `k_tgfbr1`."
      },
      {
        "name": "initial_atm",
        "label": "ATM",
        "units": "native SBML value",
        "default": 1,
        "maps_to": "oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.initial_atm",
        "description": "Initial ATM. Sets the initial value of bundled SBML symbol `ATM`."
      },
      {
        "name": "initial_src",
        "label": "SRC",
        "units": "native SBML value",
        "default": 1,
        "maps_to": "oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.initial_src",
        "description": "Initial SRC. Sets the initial value of bundled SBML symbol `SRC`."
      },
      {
        "name": "initial_bad",
        "label": "BAD",
        "units": "native SBML value",
        "default": 1,
        "maps_to": "oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.initial_bad",
        "description": "Initial BAD. Sets the initial value of bundled SBML symbol `BAD`."
      },
      {
        "name": "initial_pten",
        "label": "PTEN",
        "units": "native SBML value",
        "default": 1,
        "maps_to": "oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.initial_pten",
        "description": "Initial PTEN. Sets the initial value of bundled SBML symbol `PTEN`."
      }
    ],
    "outputs": [
      {
        "name": "atm",
        "maps_to": "oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.atm",
        "description": "ATM observable. Maps to SBML symbol `ATM`."
      },
      {
        "name": "src",
        "maps_to": "oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.src",
        "description": "SRC observable. Maps to SBML symbol `SRC`."
      },
      {
        "name": "bad",
        "maps_to": "oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.bad",
        "description": "BAD observable. Maps to SBML symbol `BAD`."
      },
      {
        "name": "pten",
        "maps_to": "oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.pten",
        "description": "PTEN observable. Maps to SBML symbol `PTEN`."
      },
      {
        "name": "shc1",
        "maps_to": "oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.shc1",
        "description": "SHC1 observable. Maps to SBML symbol `SHC1`."
      },
      {
        "name": "pkn1",
        "maps_to": "oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.pkn1",
        "description": "PKN1 observable. Maps to SBML symbol `PKN1`."
      },
      {
        "name": "state",
        "maps_to": "oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.state",
        "description": "Full raw SBML observable record for reproducibility and downstream visualisation."
      },
      {
        "name": "summary",
        "maps_to": "oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.summary",
        "description": "Change and peak summary across the simulated SBML observables."
      },
      {
        "name": "species_labels",
        "maps_to": "oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_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": "Tang2019 - Pharmacology modelling of AURKB and ZAK interaction in TNBC Lab",
  "models": [
    {
      "path": "owned/models/oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model",
      "alias": "oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model",
      "provenance": {
        "owned_path": "owned/models/oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model"
      }
    },
    {
      "path": "owned/models/visualisation",
      "alias": "visualisation",
      "provenance": {
        "owned_path": "owned/models/visualisation"
      }
    }
  ],
  "wiring": [
    {
      "to": [
        "visualisation.oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model_state"
      ],
      "from": "oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.state"
    },
    {
      "to": [
        "visualisation.oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model_summary"
      ],
      "from": "oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.summary"
    },
    {
      "to": [
        "visualisation.oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model_species_labels"
      ],
      "from": "oncology_sbml_tang2019_pharmacology_modelling_of_aurkb_and_zak_biomd0000000940_model.species_labels"
    }
  ],
  "runtime": {
    "duration": 10,
    "initial_inputs": {},
    "communication_step": 1
  },
  "description": "Aurora Kinase B and ZAK interaction model Equivalent of the stochastic model used in 'Network pharmacology model predicts combined Aurora B and ZAK inhibition in MDA-MB-231 breast cancer cells' by Tan. It can be used to explore tumor-related dynamics and compare treatment-response behavior across conditions.",
  "schema_version": "2.0"
}

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