- Code MATH2307
- Unit Value 6 units
- Offered by Mathematical Sciences Institute
- ANU College ANU Joint Colleges of Science
- Course subject Mathematics
- Areas of interest Mathematics
The course begins with a detailed discussion of sequence alignment algorithms that are critical for assessing the relatedness of DNA, RNA and amino acid sequences. We then proceed to studying Markov chains and hidden Markov models as important examples of biological models for such sequences. The main algorithms and several applications will be explained. Finally, a broad range of examples of applications of mathematics in biology, both at the molecular and macroscopic level, will be given. The course is accompanied by computer lab sessions to gain practice in the language and environment for statistical and mathematical computing and graphics, R
On satisfying the requirements of this course, students will have the knowledge and skills to:
1. Understand basic models for the evolution and comparison of biological sequences.
2. Understand and apply basic probabilistic concepts such as conditional probability, Markov chains,
and hidden Markov models.
3. Understand the main principles of mathematical modelling in biology.
Assessment will be based on:
- Three assignments (20% each; LO 1-4)
- Final exam (40%; LO 1-4)
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WorkloadThree lectures per week and regular workshops.
Requisite and Incompatibility
Tuition fees are for the academic year indicated at the top of the page.
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- Student Contribution Band:
- Band 2
- Unit value:
- 6 units
If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees. Where there is a unit range displayed for this course, not all unit options below may be available.
Offerings and Dates
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery|
|7650||22 Jul 2019||29 Jul 2019||31 Aug 2019||25 Oct 2019||In Person|