Module Search

BIOL50315: Bioinformatics

It is possible that changes to modules or programmes might need to be made during the academic year, in response to the impact of Covid-19 and/or any further changes in public health advice.

Type	Tied
Level	5
Credits	15
Availability	Available in 2023/24
Module Cap	None.
Location	Durham
Department	Biosciences

Prerequisites

None

Corequisites

None

Excluded Combinations of Modules

None

Aims

To provide students with a broad understanding of bioinformatics.
To provide students with the knowledge and skills of the R environment for data analysis and visualization in Bioinformatics.
To provide students with the knowledge and skills to analyse genomic and transcriptomic data using standard software.
To provide students with the knowledge and skills to analyse DNA and protein sequence data.
To provide students with the knowledge and skills to use public bioinformatics databases.

Content

Introduction of bioinformatics.
R environment for data analysis and visualization in Bioinformatics.
Linux and high-performance computing.
Analysis of RNA-seq data using standard software.
Analysis of small-scale mutations in genome sequencing data using standard software.
Analysis of DNA and protein sequence data.
Public bioinformatics databases.

Learning Outcomes

Subject-specific Knowledge:

Essential knowledge of the R environment for data analysis and visualization in Bioinformatics.
Essential knowledge of Linux and high-performance computing.
Essential knowledge of RNA-seq data analysis.
Essential knowledge of genome sequencing data analysis.
Essential knowledge of DNA and protein sequence data analysis.
Familiar with major public bioinformatics databases.

Subject-specific Skills:

Ability to use the R environment for data analysis and visualization in Bioinformatics.
Ability to use Linux and high-performance computing.
Ability to analyse RNAseq data using standard software.
Ability to analyse small-scale mutations in genome sequencing data using standard software.
Ability to analyse DNA and protein sequence data.
Ability to use major public bioinformatics databases.

Key Skills:

Data analysis, visualization and interpretation
Linux and high-performance computing
Hypothesis building
Problem solving

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

This module will be delivered via workshops
Summative assessment will be via coursework.

Teaching Methods and Learning Hours

Activity	Number	Frequency	Duration	Total	Monitored
Workshops	16	Twice per week	2 hours	32	Yes
Preparation and reading				118
Total				150

Summative Assessment

Component: Coursework		Component Weighting: 100%
Element	Length / Duration	Element Weighting	Resit Opportunity
Bioinformatics Report		40
Mini Project Report		60

Formative Assessment

More information

If you have a question about Durham's modular degree programmes, please visit our Help page. If you have a question about modular programmes that is not covered by the Help page, or a query about the on-line Postgraduate Module Handbook, please contact us.

Prospective Students: If you have a query about a specific module or degree programme, please Ask Us.

Current Students: Please contact your department.