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Learners

This page brings together bioinformatics training materials developed by the Sydney Informatics Hub. These resources support researchers, students, and research support staff who use computational and data-intensive approaches in the life sciences.

The materials include hands-on workshops, short courses, and recorded webinars, and are designed to be practical and accessible. Our materials are focused on real research scenarios and suitable for learners from a range of backgrounds and experience levels. Many of these materials have been developed in collaboration with partner organisations: Australian BioCommons, QCIF, NCI, Pawsey Supercomputing Research Center, UNSW Structural Biology Facility, Monash Bioinformatics Platform, and Seqera.

If you have questions about suitability, access, or training opportunities, please contact us.



Topic Course Description Workshop Dataset Slides Webinar
Bioinformatics What exactly is bioinformatics? Introduction to bioinformatics experiments
Genomics Getting started with germline genomics Introduction to germline mapping and variant calling
Transcriptomics Getting started with RNAseq Introduction to differential expression analysis with bulk RNAseq data
Transcriptomics Getting started with spatial omics Introduction to spatial transcriptomics
Functional enrichment Making sense of gene lists with FEA Introduction to functional enrichment analysis
Structural biology Protein structure prediction Introduction to structural prediction with tools like Alphafold
Pipelines Nextflow for the Life Sciences Introduction to building and runing Nextflow pipelines
Pipelines Nextflow on HPC Configure and run Nextflow pipelines on HPC
Pipelines Configuring nf-core Configure nf-core pipelines for your needs
HPC Scaling your workflows to HPC Foundational concepts of HPC as they relate to bioinformatics
HPC Introduction to NCI Gadi Quick start guide for using NCI's Gadi HPC
HPC Where to go when your bioinformatics outgrows your compute Explainer of national computational infrastructure for bioinformatics