Key facts

UNE unit code: GENE352

*You are viewing the 2024 version of this unit which may be subject to change in future.

Start
  • Trimester 1 - On Campus
  • Trimester 1 - Online
Campus
  • Armidale Campus
24/7 online support
  • Yes
Intensive schools
  • No
Supervised exam
  • No
Credit points
  • 6

Unit information

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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 1On Campus, Armidale Campus
Trimester 1Online

*Offering is subject to availability

Intensive schools

There are no intensive schools required for this unit.

Enrolment rules

Pre-requisites
QM161 or STAT100 or STAT210 or AMTH250
Restrictions
BINF350 or BINF550 or GENE350 or GENE552
Combined units

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)

profile photo of Julius Van Der Werf
Julius Van Der WerfProfessor in Animal Genetics - School of Environmental and Rural Science

Learning outcomes

Upon completion of this unit, students will be able to:

  1. demonstrate a broad and coherent theoretical and technical knowledge of the subject by working with and analysing data from high throughput genetic projects;
  2. demonstrate autonomy and use well-developed judgement to analyse and evaluate information using analytical methods relevant to modern biology;
  3. use computational tools to interpret biological data and therefore demonstrate the ability to work autonomously, analyse information and evaluate information; and
  4. use bioinformatics methods to answer biological questions and thereby demonstrating the ability to work autonomously, use well-developed judgement and transmit this knowledge to others using written and verbal methods.

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.

TitleMust CompleteWeightOfferingsAssessment Notes
End of Trimester ExamYes30%All offerings

End of Trimester Exam - Online via Moodle

No. Words: 1400

Essay and/or ProjectYes20%All offerings

Essay and/or Project

No. Words: 1500

ExaminationYes30%All offerings

Problem sets and tutorial reports - Online via Moodle

No. Words: 1400

Mid Trimester QuizYes20%All offerings

Mid Trimester Quiz - Online via Moodle

No. Words: 1000

PracticalYes 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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