CSC8305 : Computational Analysis of Complex Biological Systems

Semester 2 Credit Value: 10
ECTS Credits: 5.0


Biological systems are extremely complex and dealing with this complexity is critical in modern bioinformatics. 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 protein and gene networks. This module introduces you to the basic approaches for building and analysing biological networks using an approach based on graph theory approach 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, formal languages, 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 StudyAssessment preparation and completion101:0010:00Lecture follow-up
Scheduled Learning And Teaching ActivitiesLecture101:0010:00Lectures
Scheduled Learning And Teaching ActivitiesPractical101:0010:00Practicals
Scheduled Learning And Teaching ActivitiesSmall group teaching101:0010:00Tutorials
Guided Independent StudyProject work101:0010:00Coursework
Guided Independent StudyIndependent study501:0050:00Background reading
Teaching Rationale And Relationship

Lectures will be used to introduce the learning material and for demonstrating the key concepts by example. Students are expected to follow-up lectures within a few days by re-reading and annotating lecture notes to aid deep learning.

This is a very practical subject, and it is important that the learning materials are supported by hands-on opportunities provided by practical classes. Students are expected to spend time on coursework outside timetabled practical classes.

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 report2M1002 exercies of equal weight. Max 2,000 words each.
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