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Bioinformatics (POPH90124)
Graduate courseworkPoints: 12.5Not available in 2018
Overview
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Bioinformatics is a multidisciplinary field that combines biology with quantitative methods to help understand biological processes, such as disease progression. This unit provides a broad-ranging study of this application of quantitative methods in biology. Content includes: biology basics; statistical genetics; web-based tools, data sources and data retrieval; the analysis of single and multiple DNA or protein sequences; Hidden Markov Models and their applications; evolutionary models; phylogenetic trees; transcriptomics (gene expression microarrays and RNA-seq); use of R in bioinformatics applications.
Intended learning outcomes
To provide an introduction to the field of bioinformatics from a statistical point of view. This will include an understanding of the basic concepts of molecular biology.
Generic skills
On completion students should have developed independent problem solving, facility with abstract reasoning, clarity of written expression, sound communication of technical concepts.
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
- POPH90148 Probability and Distribution Theory
- MAST90101 Introduction to Statistical Computing OR POPH90018 Data Management & Statistical Computing
- MAST90100 Inference Methods in Biostatistics OR POPH90017 Principles of Statistical Inference
- MASTIO102 Linear Regression OR POPH90120 Linear Models
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 3 November 2022
Assessment
Additional details
Assignments 60% (three written assignments, each worth 20%, approx 6 hrs each) to be submitted during semester. Final at-home examination 40% (approx 12 hrs).
Last updated: 3 November 2022
Dates & times
Not available in 2018
Time commitment details
170 hours
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
Durbin R, Eddy S, Krogh A, Mitchison G. Biological Sequence Analysis: Probabilistic Models of proteins and nucleic acids. Cambridge University Press, 1998. (ISBN 978-0521629713)
Special Computer Requirements: "R" (freeware - coordinator will give instructions on how to download)
Resources Provided to Students: Printed course notes and assignment material will be provided to students via post.
Recommended texts and other resources
None
- Subject notes
This subject is not available in the Master of Public Health.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Graduate Diploma in Biostatistics Course Master of Biostatistics - Links to additional information
Last updated: 3 November 2022