Unit convenor and teaching staff |
Unit convenor and teaching staff
Lecturer in charge
Nino Kordzakhia
Contact via E-mail
Room 610, L6, E7A, 12 Wally's Walk
TBA
Lecturer
Balamehala Pasupathy
Contact via E-mail
Room 610 E7A 12 Wally's Walk
TBA
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Credit points |
Credit points
4
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Prerequisites |
Prerequisites
Admission to MBiotech or MSc or MDataSc or GradDipBioTech or MBiotechMCom or MBioBus or MLabQAMgt or PGCertLabQAMgt or GradDipLabQAMgt or GradCertLabQAMgt or MConsBiol or GradDipConsBiol or MMarScMgt
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Corequisites |
Corequisites
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Co-badged status |
Co-badged status
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Unit description |
Unit description
This unit introduces the statistical and probabilistic concepts that are the basis for the study of bioinformatics. Topics include an introduction to probability and conditional probability, probability distributions, sampling distributions and an introduction to Markov processes. Particular attention is paid to how they relate to specific applications in the field of bioinformatics. A basic understanding of calculus will be an advantage.
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Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
On successful completion of this unit, you will be able to:
Tutorial Work
In the case when a student is unable to attend the tutorial due to unavoidable circumstances, the student must apply for special consideration via https://ask.mq.edu.au/
In the case of a late submission of a Tutorial Work, if no special consideration has been granted, 10% of the earned mark will be deducted for each day that a Tutorial Work, is late, up to a maximum of 50%. After 5 days, counted including weekends and public holidays, a mark of 0% will be awarded. NOTE: It is not the intention of this late penalty policy to cause a student to fail the unit when they have submitted their assignment no more than 5 days after the due date and they would have otherwise passed. In this case, if deductions for late submissions result in the final unit mark for a student being less than 50, when otherwise it would have been 50 or greater, the student's final mark will be exactly 50.
Test
You are permitted ONE A4 page of paper containing reference material printed or handwritten on both sides.
Calculators will be needed but must not be of the text/programmable type.
In the case when a student is unable to attend the test due to unavoidable circumstances, the student must apply for special consideration via https://ask.mq.edu.au/
Practical Test
The unit material distributed via iLearn is permitted. You may bring to the practical test a hard copy of your lecture and tutorial notes.
In the case when a student is unable to attend the test due to unavoidable circumstances, the student must apply for special consideration via https://ask.mq.edu.au/
Name | Weighting | Hurdle | Due |
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Tutorial Work 1 | 10% | No | Week 3 |
Test 1 | 20% | No | Week 5 |
Tutorial Work 2 | 10% | No | Week 7 |
Tutorial Work 3 | 10% | No | Week 9 |
Test 2 | 20% | No | Week 11 |
Practical Test | 30% | No | Week 13 |
Due: Week 3
Weighting: 10%
The worksheet will be handed out in the second hour of the tutorial and is to be submitted via iLearn site of the unit before 23:55 on the day of the tutorial.
For the tutorial work assessment conditions see General Assessment Information.
Due: Week 5
Weighting: 20%
The Test will be held in the second hour of lecture time and will be 40 minutes long.
For the test conditions see General Assessment Information.
Due: Week 7
Weighting: 10%
The worksheet will be handed out in the second hour of the tutorial and is to be submitted via iLearn site of the unit before 23:55 on the day of the tutorial.
For the tutorial work assessment conditions see General Assessment Information.
Due: Week 9
Weighting: 10%
The worksheet will be handed out in the second hour of the tutorial and is to be submitted via iLearn site of the unit before 23:55 on the day of the tutorial.
For the tutorial work assessment conditions see General Assessment Information.
Due: Week 11
Weighting: 20%
The Test will be held in the second hour of lecture time and will be 40 minutes long.
For the test conditions see General Assessment Information.
Due: Week 13
Weighting: 30%
The Practical Test will be held during tutorial time and will be 1 hour and 15 minutes long.
For the practical test conditions see General Assessment Information.
Classes
Lectures begin in Week 1. Tutorials begin in Week 2.
Students must attend two hours of lectures and two hours of tutorials per week.
The lecture notes will be made available on iLearn before the lecture.
Tutorial exercises will be set weekly and will be available on iLearn before the tutorial.
The timetable for classes can be found at https://timetables.mq.edu.au/2018/
iLearn
All unit related materials including lecture notes, tutorials and instructions for assessment tasks and administrative updates, will be posted on iLearn at
https://ilearn.mq.edu.au/login/MQ/
Software
The statistical software R will be used. This is a free software environment for statistical computing and graphics on UNIX platforms, Windows and MacOS and can be downloaded from the website
Texts and materials
There is no required textbook for this unit.
Recommended reference sources:
1. W. P. Krijnen Applied Statistics for Bioinformatics using R, 2009.
http://cran.r-project.org/doc/contrib/Krijnen-IntroBioInfStatistics.pdf
2. S. Draghici Statistics and Data Analysis for Microarrays Using R and Bioconductor. Chapman & Hall/CRC Mathematical and Computational Biology, 2nd Edition, 2012.
3. P. N. Suravajhala. Your passport to a career in bioinformatics. New Delhi: Springer, 2013.
4. W. J. Ewens and G. R. Grant. Statistical Methods in Bioinformatics, an Introduction. Springer, 2005.
5. K. Lange. Mathematical and Statistical Methods for Genetic Analysis, Statistics for Biology and Health. Springer, 2002.
Weeks |
Topics |
W1 |
Introduction |
W2 |
Discrete random variables and their characteristics |
W3 - W5 |
Hardy-Weinberg Equilibrium (HWE); Departures from HWE; Statistical testing of HWE. |
W6 - W7
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Genetic mapping; Linkage analysis |
W8-W9
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Continuous random variables and their characteristics |
W10 - W11
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Hypothesis testing and its applications |
W12-W13
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Markov Chains and their applications |
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Our postgraduates will be able to demonstrate a significantly enhanced depth and breadth of knowledge, scholarly understanding, and specific subject content knowledge in their chosen fields.
This graduate capability is supported by:
Our postgraduates will be capable of utilising and reflecting on prior knowledge and experience, of applying higher level critical thinking skills, and of integrating and synthesising learning and knowledge from a range of sources and environments. A characteristic of this form of thinking is the generation of new, professionally oriented knowledge through personal or group-based critique of practice and theory.
This graduate capability is supported by:
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Date | Description |
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21/02/2018 | Duplicated entry for teaching staff. |