• Class Number 6146
  • Term Code 3260
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
    • Prof Gavin Huttley
    • Prof Justin Borevitz
    • Prof Gavin Huttley
  • Class Dates
  • Class Start Date 25/07/2022
  • Class End Date 28/10/2022
  • Census Date 31/08/2022
  • Last Date to Enrol 01/08/2022
SELT Survey Results

This course provides an introduction to the key methods and technologies of bioinformatics as pertinent to genomics. These are the fastest growing fields of biology and perhaps science.

Bioinformatics is a rapidly growing scientific discipline at the interface of genomics, statistics and computer science that has distinct but overlapping aspects: the development of computational infrastructure (eg. algorithms, programs, databases) and their use to analyse a wide variety of biological data. Among these data, genes, transcripts and epigenetic features play a central role. Their rapid and large-scale acquisition in today's genomics, transcriptomics, proteomics and other -omics projects poses the major challenge of modern biology. The large-scale and genome-wide analysis of these data relies on advances in bioinformatics and statistics.

As computer literacy is central to bioinformatics, it is also central to this course. Accordingly, the course includes short sections on computer programming using the Python and R programming languages. We further cover advanced work practices employed during bioinformatics research, including code testing and use of version control systems. Research topics covered will include techniques for sequence comparison, population and comparative genomics, and transcript analysis.

Note: Graduate students attend joint classes with undergraduates but are assessed separately.

Learning Outcomes

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

  1. Describe and apply a variety of sophisticated work practices in bioinformatics, including computer programming.
  2. Describe and evaluate current research procedures across a range of advanced topics in bioinformatics.
  3. Evaluate and interpret current literature in areas of bioinformatic practice.
  4. Design, implement and critically evaluate research methodology in the context of advanced bioinformatic analysis of DNA sequence data.
  5. Demonstrate the ability to construct and evaluate hypotheses about genomic data from mathematical and statistical models through analytical and computational methods.

Required Resources

Students need their own computer.

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.
  • Webcam
  • 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

Staff Feedback

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

  • written comments
  • verbal comments
  • feedback to whole class, groups, individuals, focus group etc

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 Course Introduction, Critical thinking Assignment
2 Introduction to Python In class quizzes
3 Introduction to Python, In class quiz, Topic assignment
4 Sequence Comparison In class quiz, Python Topic assignment 2
5 Sequence Comparison In class quiz
6 Sequence Comparison In class quiz, Topic assignment
7 Molecular Evolution In class quiz
8 Molecular Evolution In class quizzes
9 Molecular Evolution Topic assignment
10 Mini-research project on the microbiome Topic assignment
11 Mini-research project on the microbiome
12 Mini-research project on the microbiome Topic assignment

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Critical thinking 5 % 01/08/2022 08/08/2022 2,3,4,5
Introduction to Python 20 % 15/08/2022 22/08/2022 1
Sequence comparison 25 % 19/09/2022 26/09/2022 2,3,4,5
Molecular evolution 25 % 10/10/2022 17/10/2022 2,3,4,5
Mini-research project on the microbiome 25 % 28/10/2022 11/11/2022 2,3,4,5

* 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:

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 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.


For many of the labs, there will be an in class quiz (each quiz being worth 12% of the course total). (The indicative assessment tasks list does not reflect this.)

Unless a medical certificate is provided, there will not be an opportunity to take the quizzes outside of the lab.

Instructors will announce those quizzes at the beginning of their topics.

Assessment Task 1

Value: 5 %
Due Date: 01/08/2022
Return of Assessment: 08/08/2022
Learning Outcomes: 2,3,4,5

Critical thinking

This will be a written assignment worth 5% of the entire course. Same as the BIOL3157 course.

Assessment Task 2

Value: 20 %
Due Date: 15/08/2022
Return of Assessment: 22/08/2022
Learning Outcomes: 1

Introduction to Python

Assessment tasks consist of all BIOL3157 assessment items must be completed plus an additional assignment worth 5%.

The scores from the BIOL3157 and BIOL6243 assessments are added, divided by 31.25 and multiplied by 25 to give a score out of 25.

Assessment Task 3

Value: 25 %
Due Date: 19/09/2022
Return of Assessment: 26/09/2022
Learning Outcomes: 2,3,4,5

Sequence comparison

Assessment tasks consist of all BIOL3157 assessment items must be completed plus an additional assignment worth 5%.

The scores from the BIOL3157 and BIOL6243 assessments are added, divided by 31.25 and multiplied by 25 to give a score out of 25.

Assessment Task 4

Value: 25 %
Due Date: 10/10/2022
Return of Assessment: 17/10/2022
Learning Outcomes: 2,3,4,5

Molecular evolution

Assessment tasks consist of all BIOL3157 assessment items must be completed plus an additional assignment worth 5%.

The scores from the BIOL3157 and BIOL6243 assessments are added, divided by 31.25 and multiplied by 25 to give a score out of 25.

Assessment Task 5

Value: 25 %
Due Date: 28/10/2022
Return of Assessment: 11/11/2022
Learning Outcomes: 2,3,4,5

Mini-research project on the microbiome

All BIOL3157 assessment items must be completed plus an additional question worth 5%.

The scores from the BIOL3157 and BIOL6243 assessments are added, divided by 31.25 and multiplied by 25 to give a score out of 25.

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

Due to the computational nature of the course, all assignment submission is done through the a dedicated system on the class server called nbgrader. The exceptions are strictly written assignments which will be submitted through TurnItIn on Wattle.

Hardcopy Submission

There will be no hard copy submissions.

Late Submission

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.

Returning Assignments

Assignments will be returned by the nbgrader mechanism (instructions posted on Wattle) or via Wattle.

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.

Resubmission of Assignments

Resubmission is not allowed.

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).

Prof Gavin Huttley

Research Interests

genetics, statistics, computing, bioinformatics

Prof Gavin Huttley

Prof Justin Borevitz

Research Interests

Prof Justin Borevitz

Prof Gavin Huttley
02 6125 9090

Research Interests

Prof Gavin Huttley

Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions