Workshops and courses

ELIXIR node event Systems biology: from large datasets to biological insight

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Date: 4 - 8 July 2022

This course covers the use of computational tools to extract biological insight from omics datasets. The content will explore a range of approaches - ranging from network inference and data integration to machine learning and logic modelling - that can be used to extract biological insights from varied data types. Together these techniques will provide participants with a useful toolkit for designing new strategies to extract relevant information and understanding from large-scale biological data.

The motivation for running this course is a result of advances in computer science and high-performance computing that have led to groundbreaking developments in systems biology model inference. With the comparable increase of publicly-available, large-scale biological data, the challenge now lies in interpreting them in a biologically valuable manner. Likewise, machine learning approaches are making a significant impact in our analysis of large omics datasets and the extraction of useful biological knowledge.

In-person course

We plan to deliver this course in an in-person manner onsite at our training suite at EMBL-EBI, Hinxton.  Please be aware that we are continually evaluating the ongoing pandemic situation and, as such, may need to change the format of courses at short notice. Your safety is paramount to us; you can read our COVID guidance policy for more information. All information is correct at time of publishing.

Contact: Meredith Willmott - meredith@ebi.ac.uk

Venue: European Bioinformatics Institute, Hinxton

Region: Cambridge

Country: United Kingdom

Postcode: CB10 1SD

Organizer: European Bioinformatics Institute (EBI)

Host institutions: European Bioinformatics Institute

Target audience: This course is aimed at advanced PhD students, post-doctoral researchers, and non-academic scientists who are currently working with large-scale omics datasets with the aim of discerning biological function and processes. Ideal applicants should already have some experience (ideally 1-2 years) working with systems biology or related large-scale (multi-)omics data analyses. Applicants are expected to have a working knowledge of the Linux operating system and the ability to use the command line. Experience of using a programming language (i.e. Python) is highly desirable, and while the course will make use of simple coding or streamlined approaches such as Python notebooks, higher levels of competency will allow participants to focus on the scientific methodologies rather than the practical aspects of coding and how they can be applied in their own research. We recommend these free tutorials: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux: https://training.linuxfoundation.org/free-linux-training Python tutorial: https://www.w3schools.com/python/ R tutorial: https://www.datacamp.com/courses/free-introduction-to-r Regardless of your current knowledge we encourage successful participants to use these to prepare for attending the course and future work in this area. Selected participants will also be sent materials prior to the course. These might include pre-recorded talks and required reading that will be essential to fully understand the course.

Capacity: 30

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