Date: 22 - 26 February 2021

Identify the challenges, strategies and resources for multiomics data integration using biological examples. 

The virtual course will focus on the use of public data resources and open access tools for enabling integrated working, with an emphasis on data visualisation. Working with public domain data can provide added value to data derived through a researcher’s own work and additionally  inform experimental design. This course is highly relevant in the current research scenario, where an increased volume of data across the whole spectrum of biology has created both more opportunities and challenges to identifying novel perspectives and answering questions in the life sciences. This course will focus on issues around data integration, but will not include systems biology modelling or machine learning approaches.

A major element of this course is a group project, where participants will be organised in small groups to work together on a challenge set by trainers from EMBL-EBI data resource and research teams. These will allow participants to explore the bioinformatics tools and resources introduced in the course and to apply these to a set problem, providing hands-on experience of relevance to their own research. The group work will culminate in a presentation session involving all participants on the final day of the course, giving an opportunity for wider discussion on the benefits and challenges of integrating data.

Virtual course

The course will involve participants learning via pre-recorded lectures, live presentations, and trainer Q&A sessions. The content will be delivered over Zoom, with additional text communication over Slack.

Computational practicals will be run on EMBL-EBI's virtual training infrastructure; this means there is no need to have a powerful computer to run exercises or a requirement to install complex software before the course. Trainers will be available to provide support, answer questions, and further explain the analysis during these practicals.

Participants will need to be available between the hours of 09:30-17:30 GMT each day of the course.

Keywords: Reactome pathways database , Omics Discovery Index , Multiomics

Target audience: This introductory course is aimed at biologists who are embarking on multiomics projects and computational biologists / bioinformaticians who wish to gain a better knowledge of the biological challenges presented when working with integrated datasets. Some practical sessions in the course require a basic understanding of the Unix command line and the R statistics package. If you are not already familiar with these then please ensure that you complete these free tutorials before you attend the course: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Basic R concept tutorials: www.r-tutor.com/r-introduction For advanced-level training in using large-scale multiomics data and machine learning to infer biological models you may wish to consider our course on Systems Biology: From large datasets to biological insight.

Capacity: 30


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