Malinzi2018 - Enhancement of chemotherapy using oncolytic virotherapy
Citation: Enhancement of chemotherapy using oncolytic virotherapy: Mathematical and optimal control analysis.
IA spatio-temporal mathematical model, in the form of a moving boundary problem, to explain cancer dormancy. Analysis covers temporal and spatio-temporal cases, stability, travelling waves, minimum invasion wave speeds, and numerical simulations of immune-induced tumour dormancy.
How this model is classified mathematically and dynamically.
- Model class
- Formalism
- Determinism
- Deterministic
- Time dynamics
- Continuous
- Spatial
- Compartmental
- Multiscale
- No
Organisms, entities and processes this model represents.
- Organisms
- Infectious agents
- Not recorded
- Health conditions
- Not recorded
- Biological processes
- Molecular entities
- Not recorded
- Proteins / genes
- Not recorded
The data this model consumes and produces when executed.
Parameters
| Name | Default | Unit | Meaning |
|---|---|---|---|
| f1 | 1.3398 | dimensionless | Global model parameter f1. |
| f2 | 0.25 | dimensionless | Global model parameter f2. |
| d | 3.0218 | dimensionless | Global model parameter d. |
| v1 | 0.00218 | dimensionless | Global model parameter v1. |
| s1 | 3.8835 | dimensionless | Global model parameter s1. |
| s2 | 0.5 | dimensionless | Global model parameter s2. |
| v2 | 0.7279 | dimensionless | Global model parameter v2. |
| v3 | 300 | dimensionless | Global model parameter v3. |
| u1 | 1 | dimensionless | Global model parameter u1. |
| r | 0.1 | dimensionless | Global model parameter r. |
Initial conditions
| Name | Value | Unit |
|---|---|---|
| I | 0.3 | dimensionless |
| T | 0.8 | dimensionless |
| Td | 0.1 | dimensionless |
| C | 0.000001 | dimensionless |
| R | 0.8 | dimensionless |
Data inputs
| Name | Format | Required | Purpose |
|---|---|---|---|
| Malinzi2018.xml | SBML | Required | SBML model source referenced by the SED-ML task. |
Outputs
| Name | Quantity | Unit | Format |
|---|---|---|---|
| I | concentration | dimensionless | Not recorded |
| T | concentration | dimensionless | Not recorded |
Experiment protocol
SED-ML uniform time course from initial time 0 to output end time 10 with 100 points, using KISAO:0000019.
- Timestep
- 0.1 {'value': 'time unit', 'iri': 'http://purl.obolibrary.org/obo/UO_0000003', 'ontology_label': 'time unit', 'ontology': 'uo', 'mapping_confidence': 'high'}
- Duration
- 10 {'value': 'time unit', 'iri': 'http://purl.obolibrary.org/obo/UO_0000003', 'ontology_label': 'time unit', 'ontology': 'uo', 'mapping_confidence': 'high'}
- Observables
- IT
Runtime environment, dependencies, and compute requirements.
- Language
- SBML Level 2 Version 4
- Environment
- native
No README or explicit CLI documentation is included. COPASI invocations are reconstructed from the COPASI and SED-ML artifacts.
Compute requirements
- GPU
- Not required
- Parallelism
- single
Dependencies
- runtime
- COPASI 4.27 (Build 217)
Entry points
COPASI Malinzi2018.cpsOpen and run the COPASI model, including configured analyses and plots.
COPASI Malinzi2018.sedmlExecute the SED-ML uniform time-course simulation using the SBML model.
Artifacts stored with this model.
Identifiers and integrity.
- Source
- MODEL2003050002 · revision 3
- Size
- 16 KB
- SHA-256
- Metadata review
- Approved · eb7b6c55-efae-45b9-9369-668c8a4d7346 · Oct 2026
- Contacts
- Jinghao Men · jm2187@cam.ac.ukcorresponding author · University of Cambridge
- Krishna Kumar Tiwari · ktiwari@ebi.ac.ukmaintainer · EMBL-EBI
- Jinghao Men · jm2187@cam.ac.uk
- Related
- Isbiomodels:MODEL2003050002
- Is
- External IDs
- biomodels:MODEL2003050002