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Case Studies In Computational Biology (BIOL30003)
Undergraduate level 3Points: 12.5On Campus (Parkville)
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Overview
Availability | Semester 2 |
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Fees | Look up fees |
This subject will introduce current topics in computational biology, focusing on case studies in a number of different biological areas, and applying a range of different mathematical and computational data handling approaches to solve or interrogate biological problems. Each topic will be developed through a series of lectures introducing the biological topic (relying on a fundamental knowledge of the molecular basis of life gained in second year level genetics and biochemistry subjects), the types and sources of biological data, and the relevant computational approaches, based around case studies. A series of assignments in each of these topic areas, supported by tutorial classes, will illustrate the computational methodologies as they are applied to specific biological data.
Indicative biological topics include applications of computational biology in:
- Phylogenetics, population genetics and evolution
- Ecological and environmental modeling (including geospatial and environmental decision making)
- Bio-imaging and cell tracking in cell biology
- Pathogenesis and immunology
- Structural biology
- Metabolic engineering and biotechnology
Intended learning outcomes
On completion of this subject, students should:
- Appreciate the broad range of biological topics, types of data, and computational approaches that are used in computational biology
- Have an appreciation for how different computational approaches are relevant and appropriate for specific types of biological data
- Describe the measurement technologies and sources of quantitative data in biology
- Be aware of online databases and repositories for quantitative biological data, and be able to access, download and manipulate biological data from online resources
- Understand and be able to convert a biological problem into an appropriate computational problem
Generic skills
- Time-management: the ability to meet regular deadlines while balancing competing commitments.
- Ability to bring together knowledge from different disciplines to bear on a scientific or technological problem
- Ability to find and use appropriate resources (including online)
- Ability to communicate biological and computational knowledge effectively
- Capacity for lifelong learning and professional development
- Understanding of plagiarism, respect for honesty and intellectual integrity, and for the ethics of scholarship
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
Students must have completed all of:
Code | Name | Teaching period | Credit Points |
---|---|---|---|
BCMB20002 | Biochemistry and Molecular Biology |
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
|
12.5 |
COMP20008 | Elements of Data Processing |
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
|
12.5 |
GENE20001 | Principles of Genetics | Semester 1 (On Campus - Parkville) |
12.5 |
MAST30032 | Biological Modelling and Simulation | Semester 1 (On Campus - Parkville) |
12.5 |
Corequisites
None
Non-allowed subjects
None
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
Six written assignments (10% each) based on topics developed in the lectures, each culminating in a short report, totalling not more than 3000 words (6x 500 words), due in weeks 3, 5, 7, 8, 10 and 12 (60%). One written 2-hour end-of-semester examination due in the examination period (40%). There is a hurdle requirement of a minimum 50% mark on examination for satisfactory completion.
Last updated: 3 November 2022
Dates & times
- Semester 2
Principal coordinator Irene Gallego Romero Mode of delivery On Campus (Parkville) Contact hours 48 hours: 24 x one-hour lectures (2 per week) and 12 x two-hour tutorial classes (1 per week). Total time commitment 170 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
170 hours
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
There are no specifically prescribed or recommended texts for this subject.
- Related Handbook entries
This subject contributes to the following:
Type Name Major Computational Biology Informal specialisation Science-credited subjects - new generation B-SCI and B-ENG. - 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.
Last updated: 3 November 2022