ARTIFICIAL INTELLIGENCE IN BIOINFORMATICS

CSE5BIO

2020

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.

School: Engineering and Mathematical Sciences (Pre 2022)

Credit points: 15

Subject Co-ordinator: Rajalakshmi Rajasekaran

Available to Study Abroad/Exchange Students: Yes

Subject year level: Year Level 5 - Masters

Available as Elective: No

Learning Activities: N/A

Capstone subject: No

Subject particulars

Subject rules

Prerequisites: N/A

Co-requisites: N/A

Incompatible subjects: N/A

Equivalent subjects: N/A

Quota Management Strategy: N/A

Quota-conditions or rules: N/A

Special conditions: N/A

Minimum credit point requirement: N/A

Assumed knowledge: N/A

Career Ready

Career-focused: No

Work-based learning: No

Self sourced or Uni sourced: N/A

Entire subject or partial subject: N/A

Total hours/days required: N/A

Location of WBL activity (region): N/A

WBL addtional requirements: N/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.

Melbourne (Bundoora), 2020, Semester 1, Day

Overview

Online enrolment: Yes

Maximum enrolment size: N/A

Subject Instance Co-ordinator: Rajalakshmi 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.

Assessments

Assessment elementCommentsCategoryContributionHurdle%ILO*

One 3-hour examinationHurdle Requirement: To pass the subject, a pass in the examination is mandatory.

N/AN/AN/AYes50SILO2, SILO3, SILO4

Laboratory classes exercise equivalent to 100 words per laboratory class (total 1000 words)

N/AN/AN/ANo10SILO2

First assignment equivalent to 1200 wordsA written report on biological and biomedical data and their related issues using AI approaches

N/AN/AN/ANo20SILO1, SILO2, SILO3, SILO4

Second assignment equivalent to 1200 wordsA written report on various AI approaches in emerging topics such as molecular interactions and biological knowledge discovery.

N/AN/AN/ANo20SILO1, SILO2, SILO3, SILO4