Biology Teaching and Learning Centre · ANU College of Science and Medicine
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. Other topics covered include techniques for sequence comparison, population and comparative genomics. Honours pathway option (HPO) An Enrichment-type HPO is offered. Students in this option must attend 7 additional 1hr workshops, which will help develop skills necessary to undertake further research in this area. We cover a problem related to course material in considerable detail. We will review a published method and independently design and implement computational experiments to evaluate the method. This addresses LO's 3-5.
Quizzes
Learning outcomes 1
Written assignments (approx 2 across the semester)
Learning outcomes 3, 4
Coding assignment
Learning outcomes 1
Mixed written and coding assignments (approx 3 x assignments across the semester)
Learning outcomes 1, 2, 3, 4, 5
The expected workload will consist of approximately 130 hours throughout the semester including: - Face-to face component which may consist of 2 x 2 hour computer labs per week (total 48 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.
"Topics in Bioinformatics" written by Prof. Huttley, available online at https://gavinhuttley.github.io/tib/.