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BIOL3157 Bioinformatics and Functional Genomics

Later Year Course

Offered By Biology Teaching and Learning Centre
Academic Career Undergraduate
Course Subject Biology
Offered in Second Semester, 2013 and Second Semester, 2014
Unit Value 6 units
Course Description

Bioinformatics is a rapidly growing scientific discipline at the interface of molecular biology 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 ofbiological data. Among these data, genes, transcripts and proteins 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 comparable genomics, sequencing techniques, genome evolution and phylogenetics.

Learning Outcomes

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.

Workload

Three lectures per week and up to eight practical classes/computer labs

Requisite Statement

BIOL2151 or BIOL3161

Science Group C
Academic Contact Dr Georg Weiller

The information published on the Study at ANU 2013 website applies to the 2013 academic year only. All information provided on this website replaces the information contained in the Study at ANU 2012 website.

Updated:   13 Nov 2015 / Responsible Officer:   The Registrar / Page Contact:   Student Business Solutions