|Year of offer||2017|
|Subject level||Graduate coursework|
|Fees||Subject EFTSL, Level, Discipline & Census Date|
Technological advances in obtaining high throughput data from functioning cells have stimulated the development of new computational approaches to functional genomics and systems biology. This subject covers the theory and practice of the computational techniques used in genomics analysis, with an emphasis on functional genomics.
This subject is a core subject in the MSc (Bioinformatics), and is an elective in the Master of Information Technology and the Master of Engineering. It can also be taken by PhD students and by undergraduate students, subject to the approval of the lecturer.
The subject covers key algorithms used in genomics analyses, and their application. Topics include: computational analysis of microarray data; classification and clustering, and their application to functional genomics analysis; detecting variants in genomic data; next generation sequencing for DNA; next generation sequencing for RNA.
Intended learning outcomes
INTENDED LEARNING OUTCOMES (ILO)
On completion of this subject the student is expected to:
- Describe and apply key algorithms used in the analysis of genomics data
- Describe next generation DNA sequencing, and compare and contrast it with the application of next generation sequencing to RNA (RNA-seq)
- Describe the application of machine learning techniques to gene expression data, and their strengths and weaknesses
- Understand the uses and limitations of bioinformatics software tools which use these algorithms, and apply these tools to practical data analysis
- Describe the limitations of current methods in functional genomics.
Having completed this unit the student is expected to have the following skills:
- Read the current literature in functional genome analysis
- Describe current research issues in computational analysis of functional genomics data
- Investigate current genomics software tools, understand their principles and limitations, and apply them appropriately.
Eligibility and requirements
Recommended background knowledge
One semester of computer programming or equivalent experience.
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
- Project work includes two research reports spread evenly over the semester (30% in total). The total expected time commitment for project assessments is approximately 35 - 40 hours of work
- A 3-hour written examination at the end of the semester (70%).
Hurdle requirement: To pass the subject students must obtain at least:
- 50% overall
- 35/70 on the end-of-semester examination
- 15/30 on the project work.
Dates & times
- Semester 2
Principal coordinator Jan Schroeder Mode of delivery On Campus — Parkville Contact hours 36 hours, comprising of one 2-hour lecture and one 1-hour workshop per week Total time commitment 200 hours Teaching period 24 July 2017 to 22 October 2017 Last self-enrol date 4 August 2017 Census date 31 August 2017 Last date to withdraw without fail 22 September 2017 Assessment period ends 17 November 2017
Semester 2 contact information
Dr Jan Schroeder
Time commitment details
- Subject notes
LEARNING AND TEACHING METHODS
The subject will be delivered through a combination of lectures, group discussion, and tutorials. The assigned project work is also a key feature in the learning process.
INDICATIVE KEY LEARNING RESOURCES
Students will have access to lecture notes and audio recording of the lectures. Papers drawn from the current literature are posted to the LMS for each topic. Students are expected to find and read additional papers from the literature relevant to their assignments.
CAREERS / INDUSTRY LINKS
The subject provides an in-depth introduction to the two main approaches to functional genomics current today. As such the subject provides a foundation for applied and research careers in bioinformatics. Guest lectures are given by practitioners in the field.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Master of Science (Bioinformatics) Course Ph.D.- Engineering Course Doctor of Philosophy - Engineering Course Master of Data Science Course Master of Philosophy - Engineering Course Master of Science (Computer Science) Major Computer Science Informal specialisation Computer Science Informal specialisation Master of Engineering (Biomedical with Business) Informal specialisation Master of Engineering (Biomedical) Informal specialisation Master of Engineering (Software) Specialisation (formal) Biomedical Specialisation (formal) Software Specialisation (formal) Biomedical with Business
- Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
Additional information for this subject
Subject coordinator approval required