CSC8319 : Stochastic Systems Biology
- Offered for Year: 2018/19
- Module Leader(s): Dr Paolo Zuliani
- Owning School: Computing
- Teaching Location: Newcastle City Campus
|Semester 2 Credit Value:||10|
To introduce stochastic modelling of biological processes, computational methods for sequence analysis and modelling of genetic and biochemical networks.
Statistics is becoming increasingly important in bioinformatics as biological research moves into an era of predictive biology. This module builds on the stats skills acquired in MAS8401, introducing more advanced statistical techniques such as Hidden Markov models and stochastic modelling of biological pathways, that are used frequently used in modern bioinformatics.
Outline Of Syllabus
Introduction to probability modelling: independence, Markov chains, hidden Markov models. Estimation: maximum likelihood, confidence intervals. Algorithms: localised and global decoding; Baum-Welch. Implementation in R.
Introduction to biological modelling; representations of biochemical networks; chemical kinetics; stochastic kinetics; stochastic simulation algorithms.
|Guided Independent Study||Assessment preparation and completion||1||15:00||15:00||Assessed project 2|
|Guided Independent Study||Assessment preparation and completion||1||10:00||10:00||Assessed project 1|
|Scheduled Learning And Teaching Activities||Lecture||8||1:30||12:00||Formal lectures|
|Scheduled Learning And Teaching Activities||Practical||5||2:00||10:00||Practicals|
|Scheduled Learning And Teaching Activities||Drop-in/surgery||12||0:00||0:00||Office Hours in a staff office|
|Guided Independent Study||Independent study||1||53:00||53:00||Studying, practising and gaining understanding of course material|
Teaching Rationale And Relationship
Lectures and directed reading will be used to deliver the technical material. Practical computer sessions will be used to emphasise the simulation and analysis components.
The format of resits will be determined by the Board of Examiners
|Written exercise||2||M||50||Assessed project 1 (1500 words excluding figures and tables)|
|Written exercise||2||M||50||Assessed project 2 (1500 words excluding figures and tables)|
Assessment Rationale And Relationship
There will be two equally-weighted components. One will assess understanding of Markov chains and implementation of HMM-based sequence analysis algorithms. The other will assess skills in the simulation and modelling of biological processes and networks.