With the increase in the volume of data across the whole spectrum of biology, more researchers are looking to integrate omics data of different types to inform hypotheses and biological questions. This may also include public domain data, which can provide added value to data derived through researcher’s own work and inform experimental design. This introductory course will highlight the challenges that researchers face in integrating multi-omics data sets using biological examples. The course will focus on the use of public data resources and open access tools for enabling integrated working, with an emphasis on data visualisation. Please note this course does not cover statistical approaches for data integration.

Who is this course for?

This introductory course is aimed at biologists who are embarking on multi-omics projects and computational biologists / bioinformaticians who wish to gain a better understanding of the biological challenges when working with integrated datasets. No programming or command line experience is required to attend this course. Please note this course does not cover statistical approaches for data integration.

For advanced-level training in using large-scale multi-omics data and machine learning to infer biological models you may wish to consider our course on Systems Biology: From large datasets to biological insight.

What will I learn?

Learning outcomes

After this course you should be able to:

• Discuss motivations for working in an integrated manner
• Comprehend the importance of data standards and the collection of metadata
• Identify challenges for bringing different data types together
• Use a range of bioinformatics tools to organise and visualise biological data

Course content

During this course you will learn about:

• Data standards, curation and ID mapping
• Quality control for data integration
• Analysis and visualistion: Cytoscape, InterMine
• Challenges and best practice for working in an integrated manner with genomic, transcriptomic, and proteomic data

Trainers

Please read our page on application advice before starting your application. In order to be considered for a place on this course, you must do the following:

1. Complete the online application form
2. Submit a Microsoft Word (.docx) document containing three short paragraphs with a biography, work history and description of your current research interests; each paragraph should be no more than 100 words
3. Provide a letter of support from a supervisor or a senior co-worker explaining why you should be selected for this course

Please submit all documents to Frank O'Donnell (frank@ebi.ac.uk) by 12:00 GMT on Friday 23 November, 2018.

Incomplete applications will not be considered.

PLEASE NOTE: All participants will be expected to produce an A2 poster for the Poster Session - Posters are to include current research interests relevant to your current work.