Skip to main content


CSC8305 : Computational Analysis of Complex Biological Systems

  • Offered for Year: 2021/22
  • Module Leader(s): Dr Harold Fellermann
  • Owning School: Computing
  • Teaching Location: Newcastle City Campus
Semester 2 Credit Value: 10
ECTS Credits: 5.0


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 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, 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
Structured Guided LearningLecture materials161:0016:00Asynchronous online material
Scheduled Learning And Teaching ActivitiesLecture41:004:00Present-in-person lectures, else additional online sessions
Guided Independent StudyAssessment preparation and completion46:0024:00Lecture follow-up, including time for practicals
Guided Independent StudyAssessment preparation and completion212:0024:00Practical/Lab report assessment
Scheduled Learning And Teaching ActivitiesDrop-in/surgery42:008:00Synchronous PiP session, if available. Else additional synchronous online sessions
Guided Independent StudyIndependent study46:0024:00Background reading
Teaching Rationale And Relationship

Lectures 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 report2M50Max 2,000 words
Practical/lab report2M50Max 2,000 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