Course Title: Bioinformatics

Part A: Course Overview

Course Title: Bioinformatics

Credit Points: 12.00


Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

BIOL2034

City Campus

Postgraduate

135H Applied Sciences

Face-to-Face

Sem 1 2006,
Sem 1 2007,
Sem 1 2009,
Sem 1 2012,
Sem 1 2013,
Sem 1 2014,
Sem 1 2015,
Sem 2 2015,
Sem 1 2016,
Sem 2 2016

BIOL2034

City Campus

Postgraduate

171H School of Science

Face-to-Face

Sem 1 2017,
Sem 2 2017

BIOL2254

City Campus

Undergraduate

135H Applied Sciences

Face-to-Face

Sem 1 2007,
Sem 1 2012,
Sem 1 2013,
Sem 1 2015,
Sem 1 2016,
Sem 2 2016

BIOL2254

City Campus

Undergraduate

171H School of Science

Face-to-Face

Sem 1 2017,
Sem 2 2017

Course Coordinator: Dr Peter Smooker

Course Coordinator Phone: +61 3 9925 7129

Course Coordinator Email: peter.smooker@rmit.edu.au

Course Coordinator Location: Building 223, Bundoora West

Course Coordinator Availability: By Appointment


Pre-requisite Courses and Assumed Knowledge and Capabilities

There are no enforced requisite courses for Bioinformatics. However, some knowledge of genetics or molecular biology would be advantageous.


Course Description

Bioinformatics is the computational management and use of biological information to solve biological problems. This course will deliver descriptions of this rapidly evolving field, and facilitate user access to and manipulation of the biological data. Topics will include descriptions of genetic and biological databases and relevant tools available to retrieve and analyse the information within these. Descriptions of various techniques, such as evolutionary analysis, data mining, protein structure/function and computational drug discovery will be given. RMIT staff and external scientists working in the field will deliver topics. This course is designed to enable you to evaluate data using bioinformatics, and to better identify potential uses and opportunities of this data within your industry context. 

 

A computer tutorial program will accompany the lecture material whereby you will utilize Bioinformatics tools freely available on the world wide web.

 Postgraduate students are also expected to develop an integrated understanding of subject matter, demonstrate advanced judgement in the selection of materials used to support discussions and comprehensively review data analysis results in order to provide relevant, succinct interpretations of any findings.

 


Objectives/Learning Outcomes/Capability Development

This course contributes to the following Program Learning Outcomes in MC111 Master of Biotechnology: 

PLO 1: Understanding Science 

1.1 You will demonstrate an advanced understanding of biological sciences by articulating the methods of science, explaining why current biological knowledge is both contestable and testable through further inquiry, and explaining the role and relevance of biotechnology in society.

1.2 You will have an understanding of recent developments in a specialised area of biotechnology 

PLO2: Advanced skills to critically analyse and solve problems in biotechnology. 

2.1 You will demonstrate cognitive skills in mastery of advanced theoretical knowledge in biotechnology and apply this knowledge to solve complex problems in existing and new areas. 

PLO 5: Personal and professional responsibility. 

5.1 You will be accountable for individual learning and scientific work by being an independent and self-directed learner.

5.2 You will work effectively, responsibly, ethically, and safely in an individual or team context.

5.3 You will demonstrate knowledge of the regulatory frameworks and ethical principles relevant to biotechnology.

 


On successful completion of this course you should be able to:

  1.  Explain the basic principles that underpin Bioinformatics analyses, and apply these principles when analysing biological data;
  2.  Survey a selected field within Bioinformatics, synthesise information from primary literature, and coherently report your findings in a written document;
  3.  Analyse biological data using a variety of Bioinformatics tools; and
  4.  Interpret correctly the outputs from tools used to analyse biological data and make meaningful predictions from these outputs.

 


Overview of Learning Activities

You will be presented with a series of advanced lectures that illustrate both fundamental principles of Bioinformatics and the applications of these principles in particular areas. Experts in such fields will present several of the lectures. A set of computer tutorials will accompany the lectures.

 Learning will be facilitated by: 

  • your attendance at lectures where syllabus material will be presented and explained, and the subject will be illustrated with demonstrations and examples;
  • completion of computer tutorials designed to give you further practice in the application of theory and procedures, and to give feedback on your progress and understanding;
  • completion of written assignments requiring an integrated understanding of the subject matter; and
  • private study, working through the course as presented in classes and learning materials, and gaining practice at solving conceptual problems.

 Total Study Hours

A total of 120 hours is expected during this course, comprising:

Teacher-guided hours (40 hours): 12 weeks of lectures (2 hours/week) and 16 hours of computer laboratory classes.

Learner-directed hours (80 hours): e.g. reviewing lecture material, preparing assignments, preparing for computer tests.

 


Overview of Learning Resources

Lecture and computer tutorial notes will be provided through Blackboard, as will other articles of interest such as research articles and websites. No formal textbook is assigned, however students are directed to the liaison librarian..
 


Overview of Assessment

Note that:

☒This course has no hurdle requirements. 

Assessment tasks are varied and comprise two computer tests, based on the tutorials that you undertake, a major written assignment that synthesises multiple research findings and an end of semester exam.

Assessment tasks 

Early Assessment Task: Computer test 1

Weighting 15%

This assessment task supports CLOs 1, 3 and 4

This assessment provides you with early feedback.

Assessment Task 2: Computer test 2

Weighting 15%

This assessment task supports CLOs 1, 3 and 4

Assessment Task 3: Written assignment

Weighting 30%

This assessment task supports CLO 2

Assessment 4: End of semester exam

Weighting 40%

This assessment supports CLOs 1, 2 and 4

Guidelines for tests and assignments will be given, and written feedback will be supplied through Blackboard.

Postgraduates are expected to demonstrate an integrated understanding of subject matter, advanced judgement in the selection of materials used to support discussions and comprehensively review data analysis results in order to provide relevant, succinct interpretations of any findings.