UnitPostgraduate

BMS5022 Advanced bioinformatics: efficient genome, transcriptome and proteome analysis

Faculty of Medicine, Nursing and Health Sciences

BMS5022 Advanced bioinformatics: efficient genome, transcriptome and proteome analysis is a 6-credit-point, postgraduate unit from the Faculty of Medicine, Nursing and Health Sciences, offered in 2020 in Semester 2 at Clayton. It needs BMS5021.

Credit points
6
Offered in 2020
Semester 2
Clayton

This is the 2020 handbook entry. See the 2024 entry.

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Requisites

Before BMS5022

Prerequisites

Pass these before you enrol.

After BMS5022

No unit lists BMS5022 as a prerequisite in the 2020 handbook.

Enrolment rules

Corequisite: must be enrolled in one of the following course codes: C6004 or M6003 or M6030

Overview

This unit will combine theory with practise to introduce students to techniques for rapid genome, transcriptome and proteome analysis, viz., data derived from genes and proteins. It builds on Introduction of Bioinformatics (BMS5021) to cover the foundations and research frontiers of computational biology. The unit will focus on (i) aligning and modelling genomes, (ii) gene expression and epigenomics, (iii) regulatory genomics and networks, (iii) comparative genomics and evolution, and (iv) current directions in computational biology, including single-cell and cancer genomics, population genomics, deep learning and dissecting disease mechanisms. Students will practise with influential problems in large-scale biological datasets at the level of the genome, the transcriptome and the proteome and discover the techniques to analyse these datasets.

Offerings in 2020

Teaching periodCampusMode
Second semesterClaytonOn campus

Learning outcomes

When you finish this unit, you should be able to:

  1. 1

    Apply modern approaches to rapid analysis of the genome, transcriptome and proteome and data integration.

  2. 2

    Explain the relevance of data integration and modelling in computational biology.

  3. 3

    Evaluate, rate and justify current research directions in computational biology.

  4. 4

    Analyse multiple data-types in computational biology and construct appropriate analytic solutions to large-scale datasets.

  5. 5

    Formulate and construct a multi-disciplinary solution for microbiome and metagenomics datasets and design informative graphical displays and data summaries to represent the data analytic outcomes.

  6. 6

    Assemble, appraise and judge the regulatory frame work for the acquisition and use of genomics data sets

Workload and teaching

Per week: 6 hours of direct learning + 6 hours of self-directed learning.

Contacts

Chief Examiners
Professor Ramesh Rajan
Unit Coordinators
Dr Ranjeeta Menon

Common questions

What are the prerequisites for BMS5022?

You need BMS5021 before you enrol. Enrolment rules also apply.

When is BMS5022 offered?

In 2020, BMS5022 runs in Semester 2 at Clayton.

More details

Credit points
6
Study level
Postgraduate
Faculty
Faculty of Medicine, Nursing and Health Sciences
Organisational unit
School of Biomedical Sciences
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 3
Study abroad
Not available
Handbook years
20202021202220232024