Closing date: 28 June 2019

Get the skills to use public high throughput data to advance your own research!

The application of high-throughput technologies and genome-wide analysis has transformed basic and clinical research. Neuroscience in particular benefits from these approaches to gain insight into normal development, disease and injury. This has resulted in a rich landscape of publically available data which can be used by anyone to do original, publishable research.  Neuroscience in particular benefits from these approaches to gain insight into development, disease and injury. This has resulted in a rich landscape of publically available data and tools. However, employing these resources in your own research can be a daunting prospect for researchers who have important questions but lack programming skills.

This course is designed to overcome this hurdle by teaching all students how to use selected online tools to ask and answer questions, develop hypotheses or even make novel findings using the massive amount of freely available high-quality data currently available. You will also learn how different tools and datasets can be linked together to build an analysis pipelines to generate evidence supporting a hypothesis... and no coding is required! During the course you will learn about diverse data formats used in genomics and transcriptomics and how to use them.

Each week, during a 2-hour hands-on workshop, a different tool or dataset will be demonstrated and explored. Tools included in the course cover genomics, transcriptomics and proteomics and include: UCSC genome browser, Integrated Genomics Viewer (IGV), GeneNetwork, GTEX, Gene Expression Omnibus dbSNP, OMIM, NHGRI GWAS Catalog, DisGeNET, SMART, PFAM , Intact, Genemania, Gemma, Stemformatics, Cytoscape.


In addition to building your knowledge and skills, during the course every student completes an individual online research project, which complements your PhD studies. These projects, conducted during the course, are presented in a mini-symposium in the final week.


Dr Victoria Perreau (Melbourne Bioinformatics)

Dr Noel Faux (IBM Australia)

Dr Justin Rubio (Department of Pharmacology and Therapeutics)

Proposed time-frame:

Workshops: Thursdays from 10:00am - 12:00pm commencing Thursday 18 July (introduction) through Thursday 12 September.

Symposium: Thursday 10 October from 10:00am - 12:00pm.


187 Grattan St (Building 257), Floor G.

Time Commitment:

Approximately 40 hours total including:

  • 20 hours required contact time on Thursdays 10:00am - 12:00pm. This includes 9 x 2-hour hands-on workshops plus attendance at a mini-symposium of student projects.
  • An additional commitment of at least 20 hours working on individual research projects.  Students are additionally supported by voluntary weekly office hours for personalized project support.


A good understanding of molecular biology, including gene structure, transcription and translation is essential. Students must bring their own lap top computer and mouse to workshops. All software used in the workshop is freely available and you do not need to know any coding, however programmers are very welcome to apply.

Maximum class size:


Other relevant details:

Interested applicants are encouraged to contact Vicky Perreau ( for further information and to discuss project ideas before submitting an application.  This is the 5th year that this course has been offered and every project is unique.

To apply, applicants must submit a brief project description (150 words max) summarizing the research aim they propose to approach as an essential part of this workshop.

Example of what you will learn:

The image below illustrates the power of bioinformatics and the utility of online databases and tools designed for use by researchers. This expression data is from the Allen Brain Atlas Cellular taxonomy of the mouse visual cortex, a single cell RNAseq expression atlas known as Celltax. The BAM files for individual cells of interest were downloaded from the NCBI SRA data repository and then indexed and opened in IGV to view the expression of splice variants in different cell types.  This was achieved entirely using mouse clicks in web pages and only took a few minutes to complete. Viewing aligned NGS RNAseq data in this way shows how neurons typically express the long form of TrkB receptor whereas astrocytes, and some oligodendrocyte cells, express the truncated form of the receptor.

Figure Legend:  Sashimi plot illustrating use of the Integrative Genomics to examine transcript variant expression of TrkB receptor (Ntrk2) in different cell types; Astrocytes (Red), neurons (blue) and oligodendrocyte precursor cells (green) from mouse visual cortex.