This course introduces the key methods and technologies of bioinformatics as pertinent to genomics. These are the fastest growing fields of biology and perhaps science. Bioinformatics is a rapidly growing scientific discipline at the interface of genomics, statistics and computer science. It has distinct but overlapping aspects: the development of computational infrastructure (e.g. algorithms, programs, databases) and their use to analyse a wide variety of biological data. Among these data, genes, transcripts, and epigenetic features play a central role. Making sense of the rapid and large-scale data acquisition of today's genomics, transcriptomics, proteomics, and other -omics projects poses the major challenge of modern biology. Analyses of these data relies on advances in bioinformatics and statistics.
As computer literacy is central to bioinformatics, it is also central to this course. Accordingly, the course includes a brief review of the Python programming language. We further cover advanced work practices employed during bioinformatics research, including code testing and version control systems. Research topics covered will include techniques for sequence comparison, population and comparative genomics.
Note: Graduate students attend joint classes with undergraduates but are assessed separately.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
- Describe and apply a variety of sophisticated work practices in bioinformatics, including computer programming.
- Describe and logically evaluate current research procedures across a range of advanced topics in bioinformatics.
- Demonstrate the ability to reason logically about problems to which bioinformatic analysis of DNA sequence data can be applied.
- Design, implement and critically evaluate research methodology in the context of advanced bioinformatic analysis of DNA sequence data.
- Demonstrate the ability to construct and evaluate hypotheses about genomic data from mathematical and statistical models through analytical and computational methods.
Other Information
Please email rsb.studentadmin@anu.edu.au to request a permission code to enrol in this course.
Indicative Assessment
- Quizzes (4) [LO 1]
- Written assignments (approx 2 across the semester) (12) [LO 3]
- Coding assignments (4) [LO 1]
- Professional practice (5) [LO 1]
- Mixed written and coding assignments (approx 3 x assignments across the semester) (75) [LO 1,2,3,4,5]
The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.
Workload
The expected workload will consist of approximately 130 hours throughout the semester including:
- Face-to face component which may consist of a 1 hour plus 2 x 2 hour computer labs per week (total 60 hours).
- Approximately 82 hours of self directed study which will include preparation for computer labs and other assessment tasks.
Students are expected to actively participate and contribute towards discussions.
Inherent Requirements
To be determined
Requisite and Incompatibility
Prescribed Texts
"Topics in Bioinformatics" written by Prof. Huttley, available online at https://gavinhuttley.github.io/tib/.
Assumed Knowledge
The equivalent of BIOL2151 or BIOL3161, COMP1730 or COMP1100, and some statistical knowledge (equivalent to BIOL2001 or BIOL2202 or STAT1003 or STAT1008).
Fees
Tuition fees are for the academic year indicated at the top of the page.
Commonwealth Support (CSP) Students
If you 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). More information about your student contribution amount for each course at Fees.
- Student Contribution Band:
- 2
- Unit value:
- 6 units
If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found 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 |
|---|---|
| 2024 | $4440 |
- International fee paying students
| Year | Fee |
|---|---|
| 2024 | $6360 |
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.
First Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 3610 | 19 Feb 2024 | 26 Feb 2024 | 05 Apr 2024 | 24 May 2024 | In Person | N/A |
