ECOS1201 Advanced bioinformatics: genes and gene expression (5 cr)

Study level:
Advanced studies
Grading scale:
0-5
Language:
English
Responsible organisation:
Department of Biological and Environmental Science
Curriculum periods:
2024-2025, 2025-2026, 2026-2027, 2027-2028

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Advanced bioinformatics: genes and gene expression

Description

The course teaches the students to use different bioinformatics methods to analyse genetic and genomics data, so that they can understand processes affecting variation in gene expression.

The course focuses on the use of next generation sequence data to analyse transcriptomic (RNA sequencing, or RNAseq) data, although the capability to retrieve and analyse data using remote computing and analyse data using bioinformatics software are taught as skills that can be readily transferred to solve many other bioinformatics analyses.

After providing guidance about sequencing technologies and an introduction to using UNIX, the course then instructs students how to inspect data quality, clean next generation sequence data, data and then complete an de novo transcriptome assembly and analysis of differential gene expression.

The course is implemented using a series of lectures and computer-based practical exercises (supported by self-instructional handouts so that students can work at their own pace).

Students are expected to complete independent work and also work within a group to complete interpretation tasks. 

Learning outcomes

After completing the course, the student will

· be able to search and retrieve data from open sources,

· understand principles behind different types of next generation sequencing technology,

· be capable of using UNIX command line to analyse data using remote computing facilities,

· be able to use diverse bioinformatics tools to complete tasks (e.g. clean data,  assemble a transcriptome, annotate transcripts, quantify differential expression),

· be able to produce reproducible analyses, and

· be able to interpret his/her research critically and report back to others. 

Students are expected to complete independent work and also work within a group to complete interpretation tasks. 

Additional information

The course aims to complement CMBS2404 by extending the analyses of data collected in that course. 

The course is offered every other year: spring 2026, 2028.

Description of prerequisites

Recommended: BENA2008 Introduction to Bioinformatics, BENA2005 Evolutionary Biology or equivalents. Familiarity with R is useful, but not required.

Completion methods

Method 1

Description:
The course is offered every other year: spring 2026, 2028
Evaluation criteria:
1. Research diary (50%); 2. Presentation (20%); 3. Project (20%); 4. Course participation (10%). Assessment for the course is made via assessment of their participation in the class exercises, a research diary (i.e. note keeping and data reproducability) and a small project.
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Parts of the completion methods
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Participation in teaching (5 cr)

Type:
Participation in teaching
Grading scale:
0-5
Language:
English
No published teaching