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Computational Genomics (COMP90016)
Graduate courseworkPoints: 12.5Dual-Delivery (Parkville)
To learn more, visit 2023 Course and subject delivery.
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 1
Subject Coordinator
Steven Morgan
steven.morgan@unimelb.edu.au
Administrative Coordination
biomedsci-gradstudent@unimelb.edu.au
Overview
Availability | Semester 1 - Dual-Delivery |
---|---|
Fees | Look up fees |
AIM
The study of genomics is on the forefront of biology. Current laboratory technologies generate huge amounts of data and computational analysis is necessary to make sense of these data. This subject covers a broad range of approaches to the computational analysis of genomic data. You will learn the theory behind a variety of different approaches to genomic analysis, and be introduced to key tools in current use, preparing you to use existing methods appropriately as well as developing new ways to analyse genomic data. You will also have opportunities to apply your skills in workshops and assignments using both existing computational genomics tools and writing your own custom Python functions.
The subject is a core requirement in the MSc (Bioinformatics), and is an elective in other courses. It can also be taken by PhD students and by undergraduate students, subject to the approval of the subject coordinator.
INDICATIVE CONTENT
This subject covers the computational analysis of several important forms of genomic data. Topics include computational resource management, reproducible research principles, genomics workflows, sequence alignment, genome annotation, parallel computing, metagenomics and single-cell sequencing. The subject domain rapidly progresses, and subject content is regularly revised and updated.
Practical work includes writing bioinformatics functions with Python code, accessing genomics data repositories and using popular command-line tools.
Intended learning outcomes
On completion of this subject the student is expected to:
- Use and manipulate a range of data formats used in computational genomics
- Identify and describe commonly used computational approaches to processing genomic data and appropriately apply them
- Discuss the advantages and disadvantages of a variety of algorithms that underpin computational genomic analyses
- Design analysis workflows for novel scenarios using tools and methods discussed in the subject
- Write simple Python programs and use programming libraries to complete computational genomics tasks
- Describe current research issues in computational genomics and related fields
- Explain the role of computational genomics in solving modern biological challenges
Generic skills
- Independent critical thought, rational inquiry and self-directed learning and research
- Using available resources autonomously to acquire relevant knowledge
- Ability to undertake problem identification, formulation and solution
- Research data management
- Capacity for creativity and innovation
- Ability to communicate effectively with related disciplines to solve multidisciplinary problems
Last updated: 31 January 2024
Eligibility and requirements
Prerequisites
One of
Code | Name | Teaching period | Credit Points |
---|---|---|---|
COMP10001 | Foundations of Computing |
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
Summer Term (Dual-Delivery - Parkville)
|
12.5 |
COMP10002 | Foundations of Algorithms |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
COMP20005 | Intro. to Numerical Computation in C |
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
|
12.5 |
COMP90041 | Programming and Software Development |
Semester 2 (On Campus - Parkville)
Semester 1 (Dual-Delivery - Parkville)
|
12.5 |
COMP90059 | Introduction to Programming |
Semester 2 (On Campus - Parkville)
Semester 1 (Dual-Delivery - Parkville)
Summer Term (Dual-Delivery - Parkville)
|
12.5 |
OR
Admission into or selection of one of the following:
- MC-SCICMP Master of Science (Computer Science)
- MC-CS Master of Computer Science
- MC-DATASC Master of Data Science
- MC-BIOMENG Master of Biomedical Engineering
- MC-SOFTENG Master of Software Engineering
- Software specialisation (formal) in the MC-ENG Master of Engineering
- Software with Business specialisation (formal) in the MC-ENG Master of Engineering
- Biomedical specialisation (formal) in the MC-ENG Master of Engineering
- Biomedical with Business specialisation (formal) in the MC-ENG Master of Engineering
Corequisites
None
Non-allowed subjects
None
Recommended background knowledge
Completed and passed one semester of Python programming, equivalent Python programming experience, or extensive experience with another programming language.
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: 31 January 2024
Assessment
Description | Timing | Percentage |
---|---|---|
Programming Assignment 1
| From Week 4 to Week 5 | 10% |
Programming Assignment 2
| From Week 7 to Week 8 | 15% |
Programming Assignment 3
| From Week 10 to Week 11 | 15% |
One take home exam programming assignment
| Due in week 1 of the examination period | 20% |
Written examination
| During the examination period | 40% |
Hurdle requirement: To pass the subject, students must obtain at least: 50% overall (30/60) on the end-of-semester examination (this requirement is for the exam and the programming assignment during exams); and 20/40 on the project work | N/A |
Last updated: 31 January 2024
Dates & times
- Semester 1
Principal coordinator Steven Morgan Mode of delivery Dual-Delivery (Parkville) Contact hours 36 hours, comprised of one 2-hour lecture and one 1-hour workshop per week Total time commitment 180 hours Teaching period 27 February 2023 to 28 May 2023 Last self-enrol date 10 March 2023 Census date 31 March 2023 Last date to withdraw without fail 5 May 2023 Assessment period ends 23 June 2023 Semester 1 contact information
Subject Coordinator
Steven Morgan
steven.morgan@unimelb.edu.auAdministrative Coordination
biomedsci-gradstudent@unimelb.edu.au
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: 31 January 2024
Further information
- Texts
Prescribed texts
None
- Related Handbook entries
This subject contributes to the following:
Type Name Course Master of Data Science Course Ph.D.- Engineering Course Doctor of Philosophy - Engineering Course Master of Philosophy - Engineering Course Master of Science (Bioinformatics) Course Master of Science (Computer Science) Specialisation (formal) Software Specialisation (formal) Biomedical Specialisation (formal) Biomedical with Business Major Computer Science - 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: 31 January 2024