Part A: Course Overview

Course Title: Computational Biology

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

BIOL2575

City Campus

Postgraduate

171H School of Science

Face-to-Face

 Sem 2 2024,
Sem 1 2025

Course Coordinator: Jessica Holien

Course Coordinator Phone: +61 3 9925 7256

Course Coordinator Email: Jessica.holien@rmit.edu.au

Course Coordinator Location: Building 223, Bundoora West

Course Coordinator Availability: By Appointment


Pre-requisite Courses and Assumed Knowledge and Capabilities

Assumed Knowledge

Some basic computational knowledge and knowledge of genetics, chemistry and/or biochemistry would be advantageous


Course Description

Computational Biology is an arm of Bioinformatics. It's the computational use of biological information to solve problems. This course will deliver examples in this rapidly evolving field including descriptions of biological databases and relevant tools available to retrieve and analyse the information within these. You will learn how to utilise this data and relate it to protein structure/function and computational drug discovery. This course will enable you to get a taste of the current computational biology techniques used in academia and industry. The skills developed will aid those exploring future careers in multi-disciplinary science, particularly Bioinformatics, Biotechnology, and Drug Discovery. 


Objectives/Learning Outcomes/Capability Development

This course contributes to the program learning outcomes for MC111 Master of Biotechnology.

  • PLO1.1 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.
  • PLO1.2 You will have an understanding of recent developments in a specialised area of biotechnology
  • PLO1.3 You will demonstrate knowledge of research principles and methods applicable to biological sciences
  • PLO2.1 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.
  • PLO2.2 You will generate and evaluate complex ideas and concepts at an abstract level
  • PLO3.1 Demonstrating creativity, initiative and a high level of autonomy in research and/or professional practice
  • PLO3.2 Planning and executing a substantial research or work-based project and/or pieces of scholarship
  • PLO4 You will be able to effectively communicate concepts of biotechnology to specialist and non-specialist audiences, using a variety of presentation modes.
  • PLO5.1 You will be accountable for individual learning and scientific work by being an independent and self-directed learner
  • PLO5.2 You will work effectively, responsibly, ethically, and safely in an individual or team context
  • PLO5.3 You will demonstrate knowledge of the regulatory frameworks and ethical principles relevant to biotechnology 

For more information on the program learning outcomes for your program, please see the program guide. 


Upon successful completion of this course, you will be able to: 

  1. Critically analyse the specialised principles that underpin Computational Biology, and apply these principles autonomously when analysing biological data.
  2. Critically analyse complex biological data with expert judgement using a variety of Computational Biology tools.
  3. Evaluate and interpret critically and correctly the outputs from tools used to analyse biological data and make transmit this information to specialist and non-specialist audiences using meaningful predictions from these outputs.
  4. Understand how Computational Biology is used in real world settings and research and apply these established theories to deliver solutions to these real world problems.  


Overview of Learning Activities

You will be actively engaged in a range of learning activities such as lectorials, tutorials, practicals, laboratories, seminars, project work, class discussion, individual and group activities. Delivery may be face to face, online or a mix of both.

You are encouraged to be proactive and self-directed in your learning, asking questions of your lecturer and/or peers and seeking out information as required, especially from the numerous sources available through the RMIT library, and through links and material specific to this course that is available through myRMIT Studies Course.


Overview of Learning Resources

RMIT will provide you with resources and tools for learning in this course through myRMIT Studies Course.

There are services available to support your learning through the University Library. The Library provides guides on academic referencing and subject specialist help as well as a range of study support services. For further information, please visit the Library page on the RMIT University website and the myRMIT student portal.


Overview of Assessment

Assessment Tasks 

Assessment Task 1: Tutorial Reports 
Weighting 40% 
This assessment task supports CLOs 1, 2, and 3  

Assessment Task 2: Multiple Choice 
Weighting 20% 
This assessment task supports CLOs 1, 2 and 3  

Assessment Task 3: Final Practical 
Weighting 40% 
This assessment task supports CLOs 1, 2 and 3  

If you have a long-term medical condition and/or disability it may be possible to negotiate to vary aspects of the learning or assessment methods. You can contact the program coordinator or Equitable Learning Services if you would like to find out more.