MT5854 Mathematical Oncology

2024 to 2025 Semester 2

Curricular information may be subject to change

Further information on which modules are specific to your programme.

Key module information

SCOTCAT credits

The Scottish Credit Accumulation and Transfer (SCOTCAT) system allows credits gained in Scotland to be transferred between institutions. The number of credits associated with a module gives an indication of the amount of learning effort required by the learner. European Credit Transfer System (ECTS) credits are half the value of SCOTCAT credits.

SCQF level

SCQF level 11

The Scottish Credit and Qualifications Framework (SCQF) provides an indication of the complexity of award qualifications and associated learning and operates on an ascending numeric scale from Levels 1-12 with SCQF Level 10 equating to a Scottish undergraduate Honours degree.

Planned timetable

9am, Monday (odd weeks), Wednesday, Friday

This information is given as indicative. Timetable may change at short notice depending on room availability.

Module coordinator

Prof M A J Chaplain

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module description

Cancer is a complex disease, the second largest cause of death throughout the world (after cardiovascular diseases). Beginning with genetic mutations in a single cell, cancer progresses through several key growth phases - the avascular growth phase (nutrient delivered by diffusion of oxygen), tumour-induced angiogenesis (blood vessel growth), invasion and metastasis (spread to secondary parts of the body). Because of its complexity and multiscale nature (temporal and spatial), treatment of cancer is challenging. This module will introduce students to the mathematical modelling of the key phases of cancer growth and treatment via immunotherapy, chemotherapy and radiotherapy. The mathematical techniques used in the modelling will be nonlinear partial differential equations, and students will be exposed to current research taking place within the Mathematical Biology research group in the School of Mathematics and Statistics.

Relationship to other modules

Pre-requisites

BEFORE TAKING THIS MODULE YOU MUST PASS MT3504

Assessment pattern

2-hour written examination = 80%, coursework =20%

Re-assessment

Oral examination = 100%

Learning and teaching methods and delivery

Weekly contact

2.5 lectures (x 10 weeks), 1 tutorial (x 10 weeks)

Scheduled learning hours

The number of compulsory student:staff contact hours over the period of the module.

Guided independent study hours

120

The number of hours that students are expected to invest in independent study over the period of the module.

Intended learning outcomes

Be trained in the biomedical terminology and the corresponding biological processes, through the study of the modern and historical literature in Mathematical Oncology
Rigorously model the growth of cancer, angiogenesis, the invasion of the extracellular matrix, metastasis, and more biological processes in cancer through Ordinary-, Partial-, and Stochastic-Differential Equations
Use linear stability analysis to identify conditions for the emergence of patterns in the interaction of cancer with the environment
Develop algorithms and computer codes to simulate and study the dynamics of various cancer growth and invasion models