Algorithms for Bioinformatics (COMP90014)
Graduate courseworkPoints: 12.5On Campus (Parkville)
About this subject
Contact information
Semester 2
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 algorithms sufficiently to implement simplified but functional tools.
- Understand algorithms sufficiently to understand their use in common software.
- Understand the principles and limitations of published software algorithms and how to apply them appropriately.
Last updated: 4 March 2025
Eligibility and requirements
Prerequisites
Option 1
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| COMP90016 | Computational Genomics | Semester 1 (On Campus - Parkville) |
12.5 |
Option 2
Admission into the MC-SCIBIF Master of Science (Bioinformatics)
AND
Completion of 50 points of core subjects
Option 3
Admission into the MC-CS Master of Computer Science
Corequisites
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: 4 March 2025
Assessment
| Description | Timing | Percentage |
|---|---|---|
Three assignments due in approximately weeks 4, 8 and 11.
| From Week 4 to Week 11 | 40% |
One take home exam assignment due in the first week of the exam period.
| During the examination period | 20% |
Exam (late in the exam period)
| During the examination period | 40% |
Last updated: 4 March 2025
Dates & times
- Semester 2
Coordinator Grace Hall Mode of delivery On Campus (Parkville) Contact hours 36 hours, comprising of one 2-hour lecture and one 1-hour tutorial per week Total time commitment 166 hours Teaching period 28 July 2025 to 26 October 2025 Last self-enrol date 8 August 2025 Census date 1 September 2025 Last date to withdraw without fail 26 September 2025 Assessment period ends 21 November 2025 Semester 2 contact information
Time commitment details
200 hours
What do these dates mean
Visit this webpage to find out about these key dates, including how they impact on:
- Your tuition fees, academic transcript and statements.
- And for Commonwealth Supported students, your:
- Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement.
Last updated: 4 March 2025
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 Data Science Course Ph.D.- Engineering Course Master of Science (Bioinformatics) Course Doctor of Philosophy - Engineering Course Master of Philosophy - Engineering Specialisation (formal) Biomedical with Business 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.
- Available to Study Abroad and/or Study Exchange Students
Last updated: 4 March 2025