Date: 2 - 6 March 2020

With the increase in the volume of data across the whole spectrum of biology, more opportunities as well as challenges have been created to identify novel perspectives and answer questions in life sciences. 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 multiomics 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. This course will not include systems biology modelling or machine learning.

A major element of this course is a group project, where participants will be placed in small groups to work together on a challenge set by trainers from EMBL-EBI data resource and research teams. This allows people 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.

Venue: European Bioinformatics Institute Hinxton

Region: Cambridge

Country: United Kingdom

Postcode: CB10 1SD

Target audience: This introductory course is aimed at biologists who are embarking on multiomics projects and computational biologists / bioinformaticians who wish to gain knowledge of the biological challenges 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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