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.
Learning Outcomes
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)
Indicative Assessment
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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Workload
Three lectures per week and up to eight practical classes/computer labs.Requisite and Incompatibility
Majors
Specialisations
Fees
Tuition fees are for the academic year indicated at the top of the page.
If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
- Student Contribution Band:
- 2
- Unit value:
- 6 units
If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees. Where there is a unit range displayed for this course, not all unit options below may be available.
| Units | EFTSL |
|---|---|
| 6.00 | 0.12500 |
Course fees
- Domestic fee paying students
| Year | Fee |
|---|---|
| 2018 | $3660 |
- International fee paying students
| Year | Fee |
|---|---|
| 2018 | $5160 |
Offerings, Dates and Class Summary Links
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
Second Semester
| 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 |
