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Algorithms for Bioinformatics (COMP90014)
Graduate courseworkPoints: 12.5On Campus (Parkville)
For information about the University’s phased return to campus and in-person activity in Winter and Semester 2, please refer to the on-campus subjects page.
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 2
Douglas Pires
Please refer to the LMS for up-to-date subject information, including assessment and participation requirements, for subjects being offered in 2020.
Overview
Availability | Semester 2 |
---|---|
Fees | Look up fees |
AIMS
Technological advances in obtaining high throughput data have stimulated the development of new computational approaches to bioinformatics. This subject will cover core computational challenges in analysing bioinformatics data. We cover important algorithmic approaches and data structures used in solving these problems, and the challenges that arise as these problems increase in scale.
The 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.
INDICATIVE CONTENT
The subject covers key algorithms used in bioinformatics, with a focus on genomics. Indicative topics are: sequence alignment (dynamic algorithms and seed-and-extend), genome assembly, variant detection, phylogenetic reconstruction, genomic intervals, complexity and correctness of algorithms, clustering and classification of genomics data, data reduction and visualisation.
The subject assumes you have experience in programming and familiarity with the foundations of genomics.
Intended learning outcomes
On completion of this subject the student is expected to be able to:
- Understand bioinformatics data representations
- Describe the computational challenges posed by common bioinformatics analyses
- Apply important algorithms used in solving bioinformatics problems
- Design and implement algorithms and data structures to address key questions in bioinformatics
- Design and implement a toolkit of algorithmic problem-solving techniques that can be applied to a diverse range of bioinformatics tasks
- Understand the feasibility constraints imposed by computational complexity of algorithms
- Learn techniques for extracting information from data and visualising the results of analyses
Generic skills
- Understand important algorithms in bioinformatics sufficiently well to implement simplified but functional tools
- Understand important algorithms in bioinformatics sufficiently well to understand their use in common bioinformatics software tools
- Investigate new bioinformatics software tools by reading the literature, understand their principles and limitations, and apply them appropriately
Last updated: 30 October 2023
Eligibility and requirements
Prerequisites
Code | Name | Teaching period | Credit Points |
---|---|---|---|
COMP90016 | Computational Genomics | Semester 1 (On Campus - Parkville) |
12.5 |
OR
Completion of 50 points of core subjects within the MSc (Bioinformatics)
OR Entry to the MC-CS Master of Computer Science
Corequisites
None
Non-allowed subjects
None
Recommended background knowledge
One semester of computer programming or equivalent experience.
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: 30 October 2023
Assessment
Due to the impact of COVID-19, assessment may differ from that published in the Handbook. Students are reminded to check the subject assessment requirements published in the subject outline on the LMS
Description | Timing | Percentage |
---|---|---|
Two assignments due in approximately week 7 and week 12. Assignments cover Intended Learning Outcomes (ILOs) 1, 3, 4, 5 and 7.
| From Week 7 to Week 12 | 30% |
One 3-hour written examination at the end of the semester. This covers ILOs 1, 2, 4, 6, and 7.
| End of the assessment period | 70% |
Last updated: 30 October 2023
Dates & times
- Semester 2
Principal coordinator Douglas Valente Pires 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 3 August 2020 to 1 November 2020 Last self-enrol date 14 August 2020 Census date 21 September 2020 Last date to withdraw without fail 16 October 2020 Assessment period ends 27 November 2020 Semester 2 contact information
Douglas Pires
Time commitment details
200 hours
Last updated: 30 October 2023
Further information
- Texts
Prescribed texts
None
- 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 (Computer Science) Course Master of Data Science Course Master of Science (Bioinformatics) Course Doctor of Philosophy - Engineering Course Ph.D.- Engineering Course Master of Philosophy - Engineering Major Computer Science Specialisation (formal) Software Specialisation (formal) Biomedical with Business Specialisation (formal) Biomedical - 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.
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 30 October 2023