Handbook

COMP90016 Computational Genomics

Credit Points: 12.50
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2012:

Semester 1, Parkville - Taught on campus.Show/hide details
Pre-teaching Period Start not applicable
Teaching Period not applicable
Assessment Period End not applicable
Last date to Self-Enrol not applicable
Census Date not applicable
Last date to Withdraw without fail not applicable


Timetable can be viewed here.
For information about these dates, click here.
Time Commitment: Contact Hours: 36 hours, made up of 12 hr-hour lectures (one per week) and 12 one-hour workshops (one per week)
Total Time Commitment:

120 hours

Prerequisites:

None

Corequisites:

None

Recommended Background Knowledge:

One semester computer programming, or equivalent experience.

Non Allowed Subjects:

433-451 Computational Genomics

Core Participation Requirements:

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the disability support scheme can be found at the Disability Liaison Unit website: http://www.services.unimelb.edu.au/disability/

Coordinator

Dr Linda Stern

Contact

Dr Aaron Harwood

email: aharwood@unimelb.edu.au

Subject Overview:

Topics covered include:

  • Computational issues in physical mapping of DNA, in genome annotation, and in analyzing gene expression data
  • Motif extraction; methods for determining phylogenetic trees
  • RNA structure determination
  • And protein structure determination
Objectives:

On completion of this subject students should be able to:

  • Describe current research issues in bioinformatics
  • Describe the most commonly used approaches to processing genomic data, their theoretical underpinnings, and their strengths and limitations
  • Outline a variety of algorithms used for processing genomic data
  • Select algorithms appropriate to a given application
  • Critically evaluate the results obtained using different bioinformatics techniques to process genomic data
  • Write a simple bioinformatics computer program and use bioinformatics programming libraries
  • Describe the role of information theory in analysis of biological data
Assessment:
  • Four assignments spread over the semester, totaling 5,000 words or equivalent (30%)
  • And one 2-hour end-of-semester written examination (70%)

To pass the subject, students must obtain a mark of at least 35/70 on the exam and 15/30 for the assignments.

Prescribed 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 of this subject, students should have the:

  • Ability to undertake problem identificaiton, formulation and solution
  • Ability to utilise a systems approach to complex problems and to design an operational performance
  • Ability tomanage information and docmentation
  • Capacity for creativity and innovation
  • Ability to communicate effectively with the engineering team and with the community at large
Related Course(s): Bachelor of Computer Science (Honours)
Master of Biomedical Engineering
Master of Engineering in Distributed Computing
Master of Science (Bioinformatics)
Master of Science (Computer Science)
Master of Software Systems Engineering
Postgraduate Certificate in Engineering
Related Majors/Minors/Specialisations: Computer Science
Master of Engineering (Biomedical)
Master of Engineering (Software)

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