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Biological Modelling and Simulation (MAST30032)
Undergraduate level 3Points: 12.5Dual-Delivery (Parkville)
From 2023 most subjects will be taught on campus only with flexible options limited to a select number of postgraduate programs and individual subjects.
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About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 1
Overview
Availability | Semester 1 - Dual-Delivery |
---|---|
Fees | Look up fees |
This subject introduces the concepts of mathematical and computational modelling of biological systems, and how they are applied to data in order to study the underlying drivers of observed behaviour. The subject emphasises the role of abstraction and simplification of biological systems and requires an understanding of the underlying biological mechanisms. Combined with an introduction to sampling-based methods for statistical inference, students will learn how to identify common patterns in the rich and diverse nature of biological phenomena and appreciate how the modelling process leads to new insight into biological phenomena.
- Modelling: Deterministic and stochastic population-level dynamic models; agent-based computational models; and geospatial statistical models will be introduced and studied. Indicative examples will be drawn from health (e.g. infectious diseases, cell tumour growth, developmental biology), ecology (e.g. predator-prey systems, sustainable harvesting, environmental decision making) and biotechnology (e.g. biochemical and metabolic models).
- Simulation: Sampling based methods (e.g Monte Carlo simulation, Approximate Bayesian Computation) for parameter estimation and hypothesis testing will be introduced, and their importance in modern computational biology discussed.
Intended learning outcomes
On completion of this subject, students should:
- Appreciate how abstraction and simplification of biological systems through modelling can provide new insight into biological phenomena
- Be able to distinguish between different approaches to modelling (deterministic, stochastic, agent-based, statistical) and critically evaluate the suitability of these alternative approaches for particular biological problems
- Be able to develop computer programs that implement and solve simple models of biological phenomena
- Be familiar with the concept of statistical simulation and its role in testing hypotheses and understanding model behaviour
- Use models and their application to data to formally evaluate biological hypotheses
- Understand how to interpret and critique the biological modelling literature
Generic skills
In addition to learning specific skills that will assist students in their future careers in science, they will have the opportunity to develop generic skills that will assist them in any future career path. In particular
- modelling skills: the ability to abstract and generalise from observations of a complex system, providing an alternative perspective on the problem
- numerical and computer simulation skills: the ability to design simple computer programs to solve models and test hypotheses
- time-management skills: the ability to meet regular deadlines while balancing competing commitments.
Last updated: 31 January 2024
Eligibility and requirements
Prerequisites
Undergraduate students:
Undergraduate students must complete either one of the following pathways:
1. Normal Pathway
Code | Name | Teaching period | Credit Points |
---|---|---|---|
COMP10002 | Foundations of Algorithms |
Semester 2 (Dual-Delivery - Parkville)
Semester 1 (Dual-Delivery - Parkville)
|
12.5 |
AND
One of
Code | Name | Teaching period | Credit Points |
---|---|---|---|
BIOL10010 | Introductory Biology: Life's Complexity | Semester 2 (Dual-Delivery - Parkville) |
12.5 |
BIOL10011 | Biology: Life's Complexity | Semester 2 (Dual-Delivery - Parkville) |
12.5 |
BIOL10005 Genetics and The Evolution of Life
AND
Two of
Code | Name | Teaching period | Credit Points |
---|---|---|---|
BCMB20002 | Biochemistry and Molecular Biology |
Semester 2 (Dual-Delivery - Parkville)
Semester 1 (Online)
|
12.5 |
CEDB20003 | Fundamentals of Cell Biology | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
GENE20001 | Foundations of Genetics and Genomics | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
GENE20004 | Applications of Genetics and Genomics | Semester 2 (On Campus - Parkville) |
12.5 |
MIIM20001 | Principles of Microbiology & Immunology | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
GENE20002 Genes and Genomes (BSc pre-2020)
AND
One of the following subject sets (A, B, or C):
Set A:
One of
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST10006 | Calculus 2 |
Semester 1 (Dual-Delivery - Parkville)
Semester 2 (Dual-Delivery - Parkville)
Summer Term (Dual-Delivery - Parkville)
|
12.5 |
MAST10021 | Calculus 2: Advanced | Semester 2 (Dual-Delivery - Parkville) |
12.5 |
AND
One of
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST10007 | Linear Algebra |
Summer Term (Dual-Delivery - Parkville)
Semester 2 (Dual-Delivery - Parkville)
Semester 1 (Dual-Delivery - Parkville)
|
12.5 |
MAST10022 | Linear Algebra: Advanced | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
AND
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST20031 | Analysis of Biological Data | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
Set B:
One of
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST10006 | Calculus 2 |
Semester 1 (Dual-Delivery - Parkville)
Semester 2 (Dual-Delivery - Parkville)
Summer Term (Dual-Delivery - Parkville)
|
12.5 |
MAST10021 | Calculus 2: Advanced | Semester 2 (Dual-Delivery - Parkville) |
12.5 |
AND
One of
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST10007 | Linear Algebra |
Summer Term (Dual-Delivery - Parkville)
Semester 2 (Dual-Delivery - Parkville)
Semester 1 (Dual-Delivery - Parkville)
|
12.5 |
MAST10022 | Linear Algebra: Advanced | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
AND
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST10010 | Data Analysis 1 | Semester 2 (Dual-Delivery - Parkville) |
12.5 |
Set C:
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST20005 | Statistics |
Summer Term (Dual-Delivery - Parkville)
Semester 2 (Dual-Delivery - Parkville)
|
12.5 |
2. Advanced Mathematical Pathway
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST20030 | Differential Equations | Semester 2 (Dual-Delivery - Parkville) |
12.5 |
One of
Code | Name | Teaching period | Credit Points |
---|---|---|---|
COMP10001 | Foundations of Computing |
Summer Term (Dual-Delivery - Parkville)
Semester 1 (Dual-Delivery - Parkville)
Semester 2 (Dual-Delivery - Parkville)
|
12.5 |
COMP20005 | Intro. to Numerical Computation in C |
Semester 1 (Dual-Delivery - Parkville)
Semester 2 (Dual-Delivery - Parkville)
|
12.5 |
PHYC20013 | Laboratory and Computational Physics 2 |
Semester 2 (Dual-Delivery - Parkville)
Semester 1 (Dual-Delivery - Parkville)
|
12.5 |
Other evidence of competence in computer programming can also be provided to meet this pre-requisite, including passing a relevant Year 12 school subject, or a statement of achievement
from a relevant MOOC, or passing a programming competency test administered by
another University of Melbourne School.
Graduate students:
Admission into the MC-COMPBIO Master of Computational Biology
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: 31 January 2024
Assessment
Description | Timing | Percentage |
---|---|---|
One written assignment
| Week 8 | 20% |
Four laboratory exercises completed during practice classes, held at regular intervals due in weeks 4, 6, 10, 12 (10% for each exercise, requiring approximately 44 hours of work in total)*
| During the teaching period | 40% |
A written examination
| During the examination period | 40% |
Last updated: 31 January 2024
Dates & times
- Semester 1
Principal coordinator James Osborne Mode of delivery Dual-Delivery (Parkville) Contact hours 48 hours: 24 x one-hour lectures (2 per week), 12 x two-hour practice classes (1 per week) Total time commitment 170 hours Teaching period 28 February 2022 to 29 May 2022 Last self-enrol date 11 March 2022 Census date 31 March 2022 Last date to withdraw without fail 6 May 2022 Assessment period ends 24 June 2022 Semester 1 contact information
Time commitment details
170 hours
Last updated: 31 January 2024
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 Course Bachelor of Science Major Computational Biology Informal specialisation Science Discipline subjects - new generation B-SCI - 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.
- 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