Day 1 (Week 1 Monday)
| 2PM | Intro to course (LZ/EL) |
| 2:30PM | Seminar (EL): Mathematical modelling of tumour-immune interactions via discrete and continuum models |
| 3:00PM | Seminar : Immune system shapes cancer evolution and influence response to treatment |
| 4PM | Module 1.0 (EL): Introduction to mathematical modelling of biological systems |
| 5PM | Module 2.0 (LZ): Introduction genomic analysis of cancer datasets |
| 5:45PM | Welcome Ceremony |
Day 2 (Week 1 Tuesday)
| 9:30AM – 12:30PM | Module 1.1/1.2 (EL): Qualitative analysis of ODE models in R (examples: exponential, logistic and gompertz model) |
Day 3 (Week 1 Wednesday)
| 9:30AM – 12:30PM | Module 2.1/2.2 (LZ): Fundamentals of data science and genomics (Part 1 and Part 2) |
Day 4 (Week 1 Thursday)
| 9:30AM – 10:45AM | Module 1.3 (EL): Qualitative analysis of ODE models in R^2: linear systems |
| 11:15AM – 12:30 | Module 2.3 (LZ): Analysis of genomic data in cancer |
| 2PM – 3:30PM | Poster Session |
Day 5 (Week 1 Friday)
| 9:30AM – 10:45AM | Module 1.4 (EL): Qualitative analysis of ODE models in R^2: nonlinear systems (example: Lotka-Volterra model, tumour-immune interaction model) |
| 11:15AM – 12:30 | Module 2.4 (LZ): Integration of multi-omics data |
| 12:30 – 2PM | Pizza – Lunch |
Day 6 (Week 2 Monday)
| 2:30PM-5:30PM | Module 1.5/1.6 (EL): Numerical schemes for ODEs (practical session) and introduction to discrete and stochastic modelling |
Day 7 (Week 2 Tuesday)
| 9:30AM -12:30PM | Module 2.5/2.6 (ADG): Machine learning for tumour profiling. |
Day 8 (Week 2 Wednesday)
| 9:30AM -12:30PM | Seminars / Final Day / Networking / Closing remarks |
Additional Activities
- Seminars and talks: Guest experts will present current topics in the field.
- Discussion sessions: Spaces to resolve doubts and discuss progress.
- Group projects: Students will work on collaborative projects applying the knowledge acquired.