• Class Number 3580
  • Term Code 3030
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
  • COURSE CONVENER
    • Dr Conrad Burden
  • LECTURER
    • Dr Conrad Burden
  • Class Dates
  • Class Start Date 24/02/2020
  • Class End Date 05/06/2020
  • Census Date 08/05/2020
  • Last Date to Enrol 02/03/2020
SELT Survey Results

This course begins with a brief review of some of the areas of probability and statistics needed for applications to bioinformatics problems.  Typical problems addressed by bioinformaticians are identifying functionally different parts of a genome, searching DNA or protein databases to find sequences which are functionally similar to a given query sequence, or inferring the relatedness of different species by measuring the similarity of their genomes. The course will cover the mathematical theory behind algorithms commonly used by biologists and also give examples of current research. 

Furthermore, in consultation with the course lecturer, students will (i) select a research topic related to this course, and through reading of professional articles, acquire a fundamental knowledge of that topic. (ii) Write a report (2500 word limit) on the selected topic, explaining fundamental concepts and highlight key questions currently researched in the field. (iii) Demonstrate effective oral communication skills by presenting complex concepts to staff and other students in a 20-minute seminar, based on the report, as well as answer 10 minutes of questions.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

On satisfying the requirements of this course, students will have the knowledge and skills to:
  1. Explain thoroughly the fundamental concepts of specific topics in bioinformatics and their role in modern mathematics and applied contexts.
  2. Demonstrate a deep understanding of the mathematical reasoning underlying specific bioinformatics techniques.
  3. Demonstrate accurate and efficient use of specific bioinformatics techniques.
  4. Read research articles in leading professional journals in order to evaluate current research  in bioinformatics and communicate their findings in a comprehensive written report.
  5. Demonstrate capacity for original mathematical reasoning in a broader biological context through analysing, proving and explaining concepts from bioinformatics.
  6. Demonstrate an understanding of the process of developing novel quantitative techniques in biology with reference to specific material in the published scientific literature.  
  7. Effectively communicate complex quantitative biology concepts relating to their peers and academic staff, through oral presentations.

Staff Feedback

Students will be given feedback in the following forms in this course:

  • written comments
  • verbal comments in answer to questions in lectures and tutorials

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.

Class Schedule

Week/Session Summary of Activities Assessment
1 Review of probability and statistics Assignment 1 & final exam
2 Analysis of a single DNA sequence Assignment 1 & final exam
3 Analysis of a single DNA sequence Assignment 1 & final exam
4 Analysis of a single DNA sequence Assignment 2 & final exam
5 DNA and protein sequence comparison Assignment 2 & final exam
6 DNA and protein sequence comparison Assignment 2 & final exam
7 DNA and protein sequence comparison Assignment 3 & final exam
8 DNA and protein sequence comparison Assignment 3 & final exam
9 Population genetics Assignment 3 & final exam
10 Population genetics Assignment 4 & final exam
11 Population genetics Assignment 4 & final exam
12 Population genetics Assignment 4 & final exam

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Assignment 1 15 % 13/03/2020 20/03/2020 1,2,3,5
Assignment 2 15 % 03/04/2020 09/04/2020 1,2,3,5
Assignment 3 15 % 08/05/2020 15/05/2020 1,2,3,4,6
Assignment 4 15 % 29/05/2020 05/06/2020 1,2,3,4,6
Final Exam 40 % 04/06/2020 02/07/2020 1,2,3,5

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details

Policies

ANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the ANU Online website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.

Examination(s)

Please note, that where a date range is used in the Assessment Summary in relation to exams, the due date and return date for mid-semester exams indicate the approximate timeframe in which the exam will be held; the due and return date for end of semester exams indicate the approximate timeframe in which the exam will be held and the date official end of Semester results are released on ISIS. Students should consult the course wattle site and the ANU final examination timetable to confirm the date, time and venue of the exam.

Assessment Task 1

Value: 15 %
Due Date: 13/03/2020
Return of Assessment: 20/03/2020
Learning Outcomes: 1,2,3,5

Assignment 1

Written and R programming problems relating to material covered in Weeks 1 to 3. Masters level students will complete extra, more difficult questions in addition to those set for the co-taught undergraduate course MATH3353.

Assessment Task 2

Value: 15 %
Due Date: 03/04/2020
Return of Assessment: 09/04/2020
Learning Outcomes: 1,2,3,5

Assignment 2

Written and R programming problems relating to material covered in Weeks 4 to 6. Masters level students will complete extra, more difficult questions in addition to those set for the co-taught undergraduate course MATH3353.

Assessment Task 3

Value: 15 %
Due Date: 08/05/2020
Return of Assessment: 15/05/2020
Learning Outcomes: 1,2,3,4,6

Assignment 3

Written and R programming problems relating to material covered in Weeks 7 to 9. Masters level students will complete tasks related to recent research papers in addition to completing problems set for the co-taught undergraduate course MATH3353.

Assessment Task 4

Value: 15 %
Due Date: 29/05/2020
Return of Assessment: 05/06/2020
Learning Outcomes: 1,2,3,4,6

Assignment 4

Written and R programming problems relating to material covered in Weeks 10 to 12. Masters level students will complete tasks related to recent research papers in addition to completing problems set for the co-taught undergraduate course MATH3353.

Assessment Task 5

Value: 40 %
Due Date: 04/06/2020
Return of Assessment: 02/07/2020
Learning Outcomes: 1,2,3,5

Final Exam

3 hour written exam covering all aspects of the course. Masters level students will complete extra, more difficult questions in addition to those set for the co-taught undergraduate course MATH3353.


The date range indicates the start of the end of semester exam period and the date official end of semester results are released on ISIS. Please check the ANU final Examination Timetable http://www.anu.edu.au/students/program-administration/assessments-exams/examination-timetable to confirm the date, time and location of the mid-semester exam.

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. At its heart, academic integrity is about behaving ethically, committing to honest and responsible scholarly practice and upholding these values with respect and fairness.


The ANU commits to assisting all members of our community to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to be familiar with the academic integrity principle and Academic Misconduct Rule, uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with.


The Academic Misconduct Rule is in place to promote academic integrity and manage academic misconduct. Very minor breaches of the academic integrity principle may result in a reduction of marks of up to 10% of the total marks available for the assessment. The ANU offers a number of online and in person services to assist students with their assignments, examinations, and other learning activities. Visit the Academic Skills website for more information about academic integrity, your responsibilities and for assistance with your assignments, writing skills and study.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

Individual assessment tasks may or may not allow for late submission. Policy regarding late submission is detailed below:

  • Late submission permitted. Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.

Referencing Requirements

Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

Dr Conrad Burden
6125 0730
U1571037@anu.edu.au

Research Interests


Mathematical population genetics

Dr Conrad Burden

Tuesday 15:00 16:00
Tuesday 15:00 16:00
Dr Conrad Burden
6125 0730
conrad.burden@anu.edu.au

Research Interests


Dr Conrad Burden

Tuesday 15:00 16:00
Tuesday 15:00 16:00

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