Bioinformatics

Subject POPH90124 (2016)

Note: This is an archived Handbook entry from 2016.

Credit Points: 12.5
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject is not offered in 2016.

Time Commitment: Contact Hours: None
Total Time Commitment:

170 hours

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

Recommended Background Knowledge:

None

Non Allowed Subjects:

None

Core Participation Requirements:

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.

It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability

Contact

john.carlin@unimelb.edu.au

Melbourne School of Population and Global Health

OR

Currently enrolled students:

Future Students:

Subject Overview:

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.

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.

Assessment:

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).

Prescribed Texts:

Durbin R, Eddy S, Krogh A, Mitchison G. Biological Sequence Analysis: Probabilistic Modes of proteins and nucleic acids. Cambridge University Press, 1998. (ISBN 978-0521629713)

Special Computer Requirements: Stata statistical software and Excel (or equivalent)

Resources Provided to Students: Printed course notes and assignment material will be provided to students via post.

Recommended Texts:

None

Breadth Options:

This subject is not available as a breadth subject.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:

On completion students should have developed independent problem solving, facility with abstract reasoning, clarity of written expression, sound communication of technical concepts.

Links to further information: http://www.sph.unimelb.edu.au
Notes:

This subject is not available in the Master of Public Health.


Related Course(s): Graduate Certificate in Biostatistics
Graduate Diploma in Biostatistics
Master of Biostatistics
Postgraduate Diploma in Biostatistics

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