James Cook University Subject Handbook - 2022

BC5203 - Advanced Bioinformatics

Subject Description

This subject provides an overview of widely used computational methods in molecular biology. Lectures describe core concepts and techniques required to analyse, visualise and interpret datasets involving many thousands of genes, genomic variants or microbial taxa. Practicals work through concrete examples of methods covered in lectures, and introduce general purpose tools such as the R language and the unix shell to efficiently work with large biological datasets. Topics covered include an introduction to R and the unix shell, differential gene expression, finding and interpreting genomic variants and metagenomics. In this subject, students will critically evaluate and plan research involving large sequencing data and bioinformatics. Students will independently prepare a grant proposal and oral presentation, demonstrating their ability apply bioinformatics tools to questions of disease or ecological processes.

Learning Outcomes

• to critically evaluate results from widely used bioinformatic tools based on an understanding of their core concepts and assumptions
• to solve questions in molecular biology using appropriate statistical and bioinformatic techniques to analyse genomic sequencing data
• to apply the results from bioinformatics tools to make inferences on the evolutionary and cellular processes involved in disease or ecological events
• to write and debug short computer programs for the purposes of data reformatting, analysis and visualisation
• To critically analyse preliminary data forming the justification of an individually prepared grant proposal and oral presentation

Subject Assessment

• Written > Examination (centrally administered) - (30%) - Individual
• Written > Problem task - (20%) - Individual
• Written > Research report - (50%) - Individual

Note that minor variations might occur due to the continuous subject quality improvement process, and in case of minor variation(s) in assessment details, the Subject Outline represents the latest official information.

Special Assessment Requirements

Achieve an overall percentage of 50% or more; Complete all assignments and achieve an average assignment mark of at least 50%: Complete at least 6 coding assignments (delivered during tutorials) and achieve an average coding assignment mark of 50%: Pass the final exam

Assumed Knowledge:  This subject assumes that students are familiar with basic probability and statistics (equivalent to second year undergraduate level), as well as some familiarity with the R programming language. Students who are unsure if they meet the assumed knowledge requirements should contact the subject coordinator.

Availabilities