Credit points: 15

Subject outline

This subject introduces artificial intelligence (AI) in bioinformatics and biomedicine. It covers complex biological analysis, the application of AI principles, and the integration of diverse biological content through different AI technologies. On completing this subject you will be able to understand and apply AI techniques such as data modelling, machine learning, deep learning, statistical methods and data mining in Bioinformatics and Biomedicines problems. They will also understand how AI in bioinformatics technologies can be applied to DNA,RNA and protein structure and folding problems, molecular interactions, drug discovery, digital health, genetics and metabolic pathways.

SchoolEngineering and Mathematical Sciences

Credit points15

Subject Co-ordinatorRajalakshmi Rajasekaran

Available to Study Abroad/Exchange StudentsYes

Subject year levelYear Level 5 - Masters

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectNo

Subject particulars

Subject rules



Incompatible subjectsN/A

Equivalent subjectsN/A

Quota Management StrategyN/A

Quota-conditions or rulesN/A

Special conditionsN/A

Minimum credit point requirementN/A

Assumed knowledgeN/A

Career Ready


Work-based learningNo

Self sourced or Uni sourcedN/A

Entire subject or partial subjectN/A

Total hours/days requiredN/A

Location of WBL activity (region)N/A

WBL addtional requirementsN/A

Graduate capabilities & intended learning outcomes

Graduate Capabilities

Intended Learning Outcomes

01. Analyse the characteristics of biological and biomedical data using AI approaches.
02. Select and effectively use existing AI tools to solve bioinformatics tasks such as pattern recognition and gene identification.
03. Evaluate and interpret the results generated by bioinformatics tools to a high standard.
04. Clearly present data analysis results of molecular interactions and biological knowledge discovery.

Subject options

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Start date between: and    Key dates

Melbourne (Bundoora), 2021, Semester 1, Day


Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorRajalakshmi Rajasekaran

Class requirements

Laboratory ClassWeek: 11 - 22
One 2.00 hours laboratory class per week on weekdays during the day from week 11 to week 22 and delivered via face-to-face.

LectureWeek: 10 - 22
One 2.00 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.


Assessment elementCommentsCategoryContributionHurdle% ILO*
One 3-hour examination Hurdle Requirement: To pass the subject, a pass in the examination is mandatory.N/AN/AN/AYes50 SILO2, SILO3, SILO4
Laboratory classes exercise equivalent to 100 words per laboratory class (total 1000 words)N/AN/AN/ANo10 SILO2
First assignment equivalent to 1200 words A written report on biological and biomedical data and their related issues using AI approachesN/AN/AN/ANo20 SILO1, SILO2, SILO3, SILO4
Second assignment equivalent to 1200 words A written report on various AI approaches in emerging topics such as molecular interactions and biological knowledge discovery.N/AN/AN/ANo20 SILO1, SILO2, SILO3, SILO4