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Unit of study_
OLET5602: Computational Analysis for omics Data
Molecular and systems biology have become data-intensive sciences owing to the fast-growing omics technologies that enable the profiling of genome, epigenome, transcriptome, and proteome at full scale and, increasingly, at the single-cell level. Computational and statistical methodologies are now indispensable for analysing omics data generated from high-throughput technologies. This unit will introduce you to commonly used computational and statistical methods in omics data analysis. You are encouraged to use your own data to construct the models to visualise your research and interpret results. Learning the correct use of computational methods for various omics data analysis applications including your own data, you will develop an essential knowledge of methods and techniques in analysing omics data. This will provide a strong foundation for using computational approaches in omics-based molecular and systems biology research.
| Code | OLET5602 |
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| Academic unit | Mathematics and Statistics Academic Operations |
| Credit points | 2 |
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Prerequisites:
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None |
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Corequisites:
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None |
| Prohibitions:
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None |
| Assumed knowledge:
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Experience with at least one programming language. Basic computational and statistical concepts. Basic knowledge of molecular biology |
At the completion of this unit, you should be able to:
- LO1. Understand the key concepts in two foundation areas of systems biology – computational data analytics, and systems biology and omics sciences.
- LO2. Identify and match different computational methods used for various omics data analysis, and apply and evaluate them for omics data analysis.
- LO3. Find and analyse information and judge its reliability and significance.
Unit outlines
Unit outlines will be available 2 weeks before the first day of teaching for the relevant session.
- Intensive August, 2024 [Block mode] - Camperdown/Darlington, Sydney
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