- Code BIOL3157
- Unit Value 6 units
- Offered by Biology Teaching and Learning Centre
- ANU College ANU Joint Colleges of Science
- Course subject Biology
- Areas of interest Bioinformatics, Biology
Bioinformatics is a rapidly growing scientific discipline at the interface of genomics and computer science that has two distinct but overlapping aspects: the development of computer infrastructure (eg. algorithm, programs, databases) and their use to analyse a wide variety of biological data. Among these data, genes, transcripts and epigenetic variants play a central role. Their rapid and large-scale acquisition in today's genomics, transcriptomics, proteomics and other -omics projects poses the major challenge of modern biology. The large-scale and genome-wide analysis of these data is often referred to as 'functional genomics' and relies on advances in bioinformatics and high throughput technologies such as 3rd generation sequencing.
This course provides an introduction to the key methods and technologies of bioinformatics and functional genomics, the fastest growing fields of biology and perhaps science. As computer literacy is central, the course will include a short section on computer programming using the Python programming language. Topics covered will include sequence comparison techniques, genome databases searches, population and comparative genomics, sequencing techniques, genome evolution.
Upon successful completion, students will have the knowledge and skills to:
On satisfying the requirements of this course, students will have the knowledge and skills to:
- Describe and apply a variety of methods in bioinformatics and functional genomics, including computer programming. (LO1)
- Describe and evaluate current research procedures across a range of topics in bioinformatics. (LO2)
- Evaluate and interpret current literature in areas of bioinformatic practice. (LO3)
- Evaluate research methodology in the context of bioinformatic analysis of DNA sequence data. (LO4)
- Demonstrate the ability to obtain quantitative results from mathematical and statistical models through analytical and computational methods. (LO5)
Assessment will be based on: Five assignments 100% (20% ea) distributed throughout the semester including computer programming exercise - LO1,2,3,4,5.
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WorkloadThree lectures per week and up to eight practical classes/computer labs.
Requisite and Incompatibility
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- Student Contribution Band:
- Unit value:
- 6 units
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|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|7720||23 Jul 2018||30 Jul 2018||31 Aug 2018||26 Oct 2018||In Person||N/A|