Level: 6
Credit rating: 15
Pre-requisites: A knowledge of modern biology is not a course prerequisite.
Co-requisites: No Co-requisites
Lectures: 1 day per week (5 weeks)
Course lecturer: not assignedAdditional staff: view all staff

Semester	Event	Location	Day	Time	Group
Sem 1 w7-11	Lecture	2.19	Tue	09:00 - 17:00	-

Exam: 0%
Coursework: 100%
Lab: 0%

Introduction

Biology is currently undergoing a revolution. The success of the human genome project and other high-throughput technologies is creating a flood of new data. Capturing, interpreting and analysing this data provides real and significant challenges for computer scientists. This course will use biology as an exciting application domain for a wide range of CS techniques that have been developed on the course.
The course is organised in 4 sections:
1. basic introduction to modern biology and bioinformatics
2. data capture
3. data delivery
4. data analysis
Each section will commence with a short taught component delivered as research seminars. Assessments will be based on a short written report and presentations based on a case study that will be introduced at the start of the course.

Learning Outcomes

A student successfully completing this unit will have:
1. A basic understanding of the computational needs of modern biology
2. Developed an understanding of the problems inherent in communicating with scientists from a different discipline
3. Developed the ability to reflect upon and synthesize a range of computational techniques to develop effective problem solving strategies in an unfamiliar problem domain.
4. Developed the ability to communicate these strategies to non-specialists

Assessment of Learning outcomes

Learning outcomes will be assessed in the reports and presentations based on the case-study.

Contribution to Programme Learning Outcomes

Contribution to programme learning outcomes: A1 (DA), A2 (DA), B2 (DA), B3 (DA), C1 (DA), C3 (DA), C4 (DA) and D2 (DA).

Syllabus

Intro to Biology
Intro to Biology - the central dogma (2 hours)
Intro to genomics (2 hours)
Biology databases (2 hours)
Data capture
capturing microarray data (1 hour)
proteomics seminar (1 hour)
the gene ontology (1 hour)
resource meta-data (1 hour)
Data delivery
HCI and bioinformatics (2 hours)
Dealing with heterogeneous, distributed data. (2 hours)
bioinformatics and the grid (2 hours)
Data analysis
Integrated approaches to post-genome data (2 hours)