CSC8305 : Computational Analysis of Complex Biological Systems
- Offered for Year: 2023/24
- Module Leader(s): Dr Harold Fellermann
- Owning School: Computing
- Teaching Location: Newcastle City Campus
Semesters
| Semester 2 Credit Value: | 10 |
| ECTS Credits: | 5.0 |
Aims
Biological systems are extremely complex and dealing with this complexity is critical in modern bioinformatics, neurosciences and synthetic biology. Postgenomic bioinformatics and systems biology seek to study organisms at a holistic level often by constructing and studying models of biological interactions, such as those found in protein, gene and neural networks. This module introduces students to the basic approaches for building and analysing biological networks using an approach based on graph theory and then discusses methods for analysing the dynamics of such systems.
Outline Of Syllabus
Understanding how to analyse complex biological systems in computational and mathematical terms.
Understanding of fundamental ideas from graph theory, nonlinear and symbolic dynamics, complexity theory, statistics and probability theory in the context of computational analysis and modelling of complex biological systems.
Appropriate application of theoretical concept to analyse and model existing biological systems (e.g., protein interaction systems).
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Guided Independent Study | Assessment preparation and completion | 4 | 5:00 | 20:00 | Lecture follow-up, including time for practicals |
| Scheduled Learning And Teaching Activities | Lecture | 8 | 1:00 | 8:00 | Present-in-person lectures |
| Structured Guided Learning | Lecture materials | 16 | 1:00 | 16:00 | Asynchronous online material |
| Guided Independent Study | Assessment preparation and completion | 2 | 12:00 | 24:00 | Practical/Lab report assessment |
| Scheduled Learning And Teaching Activities | Practical | 4 | 2:00 | 8:00 | Practicals |
| Guided Independent Study | Independent study | 4 | 6:00 | 24:00 | Background reading |
| Total | 100:00 |
Teaching Rationale And Relationship
Lecture materials are used for the delivery of theory and explanation of methods, illustrated with examples. Lecture follow-up, e.g. quizzes and exercises, are associated with each lecture topic in order to provide sufficient hands-on training and rapid feedback on understanding. Scheduled sessions are used both for solution of problems and work requiring extensive computation and to give insight into the ideas/methods studied.
Students aiming for 1st class marks are expected to widen their knowledge beyond the content of lecture notes through background reading.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Practical/lab report | 2 | M | 100 | Max 2000 words |
Formative Assessments
| Description | Semester | When Set | Comment |
|---|---|---|---|
| Practical/lab report | 2 | M | Max 1,000 words |
Assessment Rationale And Relationship
The practical will provide an evaluation of the understanding of key concepts and the application of key ideas about computational analysis of complex biological systems, and evaluate their ability to apply concepts learnt in the lectures.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- CSC8305's Timetable