Algorithms for Functional Genomics (COMP90014)
Graduate courseworkPoints: 12.5On Campus (Parkville)
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 construction, 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
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.
Generic skills
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.
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
None
Corequisites
None
Non-allowed subjects
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: 3 November 2022
Assessment
Additional details
- Two assignments due in approximately week 7 and week 12 (30% in total). The total expected time commitment for project assessments is approximately 35 - 40 hours of work. Assignments cover Intended learning Outcomes ILOs 1, 3, 5, 6 and 7.
- A 3-hour written examination at the end of the semester (70%). This covers ILOs 2, 3,
- 4, 6, and 7.
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.
Last updated: 3 November 2022
Dates & times
- Semester 2
Principal coordinators Clare Sloggett and Clare Sloggett 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 23 July 2018 to 21 October 2018 Last self-enrol date 3 August 2018 Census date 31 August 2018 Last date to withdraw without fail 21 September 2018 Assessment period ends 16 November 2018
Time commitment details
200 hours
Last updated: 3 November 2022
Further information
- Texts
- 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 Philosophy - Engineering Course Master of Science (Bioinformatics) Course Master of Data Science Course Doctor of Philosophy - Engineering Course Ph.D.- Engineering Major Computer Science Specialisation (formal) Biomedical with Business Informal specialisation Computer Science Specialisation (formal) Software 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.
Please note Single Subject Studies via Community Access Program is not available to student visa holders or applicants
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
Last updated: 3 November 2022