- Class Number 3065
- Term Code 3230
- Class Info
- Unit Value 6 units
- Mode of Delivery In Person
- Dr Xia Hua
- Dr Xia Hua
- Class Dates
- Class Start Date 21/02/2022
- Class End Date 27/05/2022
- Census Date 31/03/2022
- Last Date to Enrol 28/02/2022
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.
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:
- Explain thoroughly the fundamental concepts of specific topics in bioinformatics and their role in modern mathematics and applied contexts.
- Demonstrate a deep understanding of the mathematical reasoning underlying specific bioinformatics techniques.
- Demonstrate accurate and efficient use of specific bioinformatics techniques.
- Read research articles in leading professional journals in order to evaluate current research in bioinformatics and communicate their findings in a comprehensive written report.
- Demonstrate capacity for original mathematical reasoning in a broader biological context through analysing, proving and explaining concepts from bioinformatics.
- Demonstrate an understanding of the process of developing novel quantitative techniques in biology with reference to specific material in the published scientific literature.
- Effectively communicate complex quantitative biology concepts relating to their peers and academic staff, through oral presentations.
Recommended student system requirements
ANU courses commonly use a number of online resources and activities including:
- video material, similar to YouTube, for lectures and other instruction
- two-way video conferencing for interactive learning
- email and other messaging tools for communication
- interactive web apps for formative and collaborative activities
- print and photo/scan for handwritten work
- home-based assessment.
To fully participate in ANU learning, students need:
- A computer or laptop. Mobile devices may work well but in some situations a computer/laptop may be more appropriate.
- Speakers and a microphone (e.g. headset)
- Reliable, stable internet connection. Broadband recommended. If using a mobile network or wi-fi then check performance is adequate.
- Suitable location with minimal interruptions and adequate privacy for classes and assessments.
- Printing, and photo/scanning equipment
For more information please see https://www.anu.edu.au/students/systems/recommended-student-system-requirements
Students will be given feedback in the following forms in this course:
- written comments
- verbal comments in answer to questions in lectures and tutorials
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.
|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|
Refer to the ANU Class Timetable and the course Wattle site.
|Assessment task||Value||Due Date||Return of assessment||Learning Outcomes|
|Assignment 1||15 %||11/03/2022||25/03/2022||1,2,3,5|
|Assignment 2||15 %||01/04/2022||15/04/2022||1,2,3,5|
|Assignment 3||15 %||06/05/2022||20/05/2022||1,2,3,4,6|
|Assignment 4||15 %||27/05/2022||11/06/2022||1,2,3,4,6|
|Final Exam||40 %||02/06/2022||30/06/2022||1,2,3,5|
* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details
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:
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 Academic Integrity . 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.
In Semester 1 2022, this course is delivered on campus with adjustments for remote participants. Timetabled Lectures and Workshops will also be run as a simultaneous Zoom session to enable remote students to follow in real time and to interact with the lecturer/demonstrator.
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 mode of the exam.
Assessment Task 1
Learning Outcomes: 1,2,3,5
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
Learning Outcomes: 1,2,3,5
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
Learning Outcomes: 1,2,3,4,6
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
Learning Outcomes: 1,2,3,4,6
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
Learning Outcomes: 1,2,3,5
48 hour take-home 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 mode of the end of semester exam.
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.
You will be required to agree to a declaration as part of the submission of your assignments, that will record your understanding of ANU academic integrity principles. Please keep a copy of the assignment for your records. MATH6208 does not use Turnitin, having been granted an exemption.
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 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.
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.
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).
- ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
- ANU Diversity and inclusion for students with a disability or ongoing or chronic illness
- ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
- ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
- ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
- ANUSA supports and represents undergraduate and ANU College students
- PARSA supports and represents postgraduate and research students
Mathematical Biology, Bioinformatics, Biostatistics
Dr Xia Hua