Key facts
UNE unit code: GENE552
*You are viewing the 2025 version of this unit which may be subject to change in future.
- Trimester 1 - On Campus
- Trimester 1 - Online
- Armidale Campus
- Yes
- No
- No
- 6
Unit information
In an era of rapid technological innovation in science, data plays an increasingly critical role in change and discovery. This flexibly delivered unit provides you with an understanding of the latest genomic technologies, invaluable in a range of scientific disciplines.
You will be introduced to the concepts and cutting-edge methods needed to work with and analyse data from modern genomic platforms.
Topics explored include genome wide association studies, genomic prediction of genetic merit and disease risk, reconstruction of phylogenies and population diversity, DNA sequencing, analysis of gene expression data, and methods for search sequence alignment, genes and gene ontologies in biological databases.
Alongside this conceptual background, you will hone your applied skills. Using real datasets, you will gain hands-on experience working with different technologies and examples of analyses on the R-platform, applying your knowledge to build and use bioinformatics solutions.
Offerings
For further information about UNE's teaching periods, please go to Principal Dates.
Teaching period | Mode/location |
---|---|
Trimester 1 | On Campus, Armidale Campus |
Trimester 1 | Online |
*Offering is subject to availability
Intensive schools
There are no intensive schools required for this unit.
Enrolment rules
Notes
R and various bioinformatics software packages are used throughout the unit; The School of Environmental and Rural Science considers all practical/laboratory/tutorial activities as essential to student learning. Attendance and participation in all practical/laboratory/tutorial classes (sessions) is mandatory - exemptions will not be granted without supporting evidence.
Please refer to the student handbook for current details on this unit.
Unit coordinator(s)
Learning outcomes
Upon completion of this unit, students will be able to:
- demonstrate an advanced and integrated knowledge of the subject by working with and analysing data from high throughput genetic projects;
- demonstrate autonomy and use expert judgement to analyse critically and reflect on information using analytical methods relevant to modern biology;
- use computational tools to interpret biological data and therefore demonstrate the ability to work autonomously, critically analyse information and reflect on information;
- use bioinformatics methods to answer biological questions, and thereby demonstrating the ability to work autonomously, use expert judgement and transmit this knowledge to a specialist and non-specialist audience using written and verbal methods; and
- develop the ability to undertake research and apply established theories to a body of knowledge by developing bioinformatics solutions for high throughput genetic projects.
Assessment information
Assessments are subject to change up to 8 weeks prior to the start of the teaching period in which you are undertaking the unit.
Title | Must Complete | Weight | Offerings | Assessment Notes |
---|---|---|---|---|
End of Trimester Examination | Yes | 30% | All offerings | End of Trimester Examination - Online Moodle No. Words: 1400 |
Essay and/or Project | Yes | 20% | All offerings | Essay and/or Project No. Words: 2500 |
Examination | Yes | 30% | All offerings | Problem sets and tutorial reports - Online via Moodle No. Words: 1400 |
Mid Trimester Quiz | Yes | 20% | All offerings | Mid Trimester Quiz - Online Moodle No. Words: 1000 |
Practical | Yes | All offerings | The School of Environmental and Rural Science considers all practical/laboratory/tutorial activities as essential to student learning. Attendance and participation in all practical/laboratory/tutorial classes (sessions) is mandatory - exemptions will not be granted without supporting evidence. |
Learning resources
Textbooks are subject to change up to 8 weeks prior to the start of the teaching period in which you are undertaking the unit.
Note: Recommended material is held in the University Library — purchase is optional.
Primer to Analysis of Genomic Data using R
ISBN: 9783319144740
Gondro, C., Spring 2015
Text refers to: All offerings
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