GNA5012 Applied bioinformatics
Faculty of Science
GNA5012 Applied bioinformatics is a level 5, 6-credit-point, postgraduate unit from the Faculty of Science. It isn't offered in 2021. It has no prerequisites.
- Credit points
- 6
- Offered in 2021
- Not offered
This is the 2021 handbook entry. See the 2027 entry.
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Requisites
Before GNA5012
No prerequisites or corequisites besides the enrolment rules below.
After GNA5012
No unit lists GNA5012 as a prerequisite in the 2021 handbook.
Enrolment rules
COREQUISITE: Must be enrolled in Master of Genome Analytics (or with permission from the unit coordinator)
PROHIBITION: GEN3010
Equivalent units
The same content under another code. Only one of them counts.
Overview
With advancements in high-throughput data generation technologies, we are now able to generate incredible volumes of data from genome-scale experiments. Biologists need to work with this large volume of data in various digital forms to extract biological knowledge from it.
Bioinformatics is an interdisciplinary field that deals with processing, analysis, and management of biological information using computer science and information technologies.
This unit will assist you to develop essential bioinformatics skills and focuses on the practical use of bioinformatics methods and resources for the analysis of nucleotide and protein sequences, as well as results from omics studies, with emphasis on their evolutionary underpinnings and statistical foundations. You will explore the basic concepts underlying bioinformatics algorithms for assembly, alignment and pattern finding. You will gain experience in working with data from –omics studies, and learn data type-specific methods to perform gene/protein expression analysis, clustering, network analysis, and data visualisation.
Offerings in 2021
The 2021 handbook lists no offerings for GNA5012.
Learning outcomes
When you finish this unit, you should be able to:
- 1
Evaluate current high-throughput techniques to generate omics data and apply standard workflows to analyse them;
- 2
Investigate gene set enrichment, network analysis and data visualisation protocols;
- 3
Evaluate genome assemblies and underlying algorithms using short and long read sequencing data;
- 4
Perform basic computer programming with case studies involving DNA pattern finding;
- 5
Compare and contrast machine learning applications in biology;
- 6
Demonstrate team work, scientific communication and peer to peer learning and feedback.
Workload and teaching
- Two hours of lecture material;
- 3-hours of computer lab practical or equivalent and
- Seven hours of independent study per week
Contacts
- Unit Coordinators
- Dr Sonika Tyagi
- Chief Examiners
- Dr Sonika Tyagi
Common questions
What are the prerequisites for GNA5012?
GNA5012 has no prerequisites, but enrolment rules apply.
When is GNA5012 offered?
GNA5012 has no offerings listed in the 2021 handbook.