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EBI

Virtual course by EMBL-EBI: Microscopy data analysis: machine learning and the BioImage Archive

This virtual course will show how public bioimaging data resources, centred around the BioImage Archive, enable and enhance machine learning based image analysis. The content will explore a variety of data types including electron and light microscopy and miscellaneous or multi-modal imaging data at the cell and tissue scale. Participants will cover contemporary biological image analysis with an emphasis on machine learning methods, as well as how to access and use images from databases.

Applications close: 19 January 2025

Date: 31 March - 04 April 2025

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EMBL- EBI virtual course: Cancer genomics and transcriptomics

This course will focus on the analysis of data from genomic studies of cancer. It will also highlight the application of transcriptomic analysis and single-cell technologies in cancer. Talks and interactive sessions will give an insight into the bioinformatic concepts required to analyse such data, whilst practical sessions will enable the participants to apply statistical methods to the analysis of cancer genomics data under the guidance of the trainers.

Application deadline: 09.02.2025

Date: 12 - 16 May 2025

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EMBL- EBI: Introduction to metabolomics analysis

This course is aimed at researchers who are new to the field of metabolomics and wish to learn about the process of conducting a metabolomics study. The course will benefit those who are planning to integrate metabolomics into their work, either moving into the field or as an investigator from other -omics. We will primarily focus on a basic introduction to metabolomics with worked examples using a predesigned LC-MS analysis workflow.

Application deadline: 02 February 2025

Date: 20 - 23 May 2025

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Course in EBI, UK: Gene-environment interactions in human health and disease

This introductory course is aimed at MRes/PhD students, researchers, clinicians, and other professionals working in the fields of genomics, exposomics, epidemiology, or toxicology with an interest in understanding how interactions between genes and the environment underlie human phenotypes. The course will cover the underlying concepts, computational resources, and computational modelling methods available to investigate interactions between genes and the environment (including social, biological, and physical exposures).

Registration deadline: 15 December 2024

Date: 17 - 21 March 2025

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Webinar by EMBL-EBI: Bioinformatic approaches to understand the role of the human microbiome in health and disease

This webinar will provide an overview of current metagenomic approaches to study the human microbiome and introduce several statistical methods that can be used to link its composition and function to different human phenotypes and populations. This webinar is suitable for those interested in studying the microbiomes of any environment or host. Although the presentation will be focused on the human microbiome, the methods and techniques discussed will also be applicable to other microbial ecosystems. No prior knowledge of bioinformatics is required, but undergraduate level knowledge of biology would be useful.

Date & Time: Mar 6, 2024 05:30 PM

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Course at EMBL-EBI: Summer school in bioinformatics

European Bioinformatics Institute United Kingdom in association with Elixir Estonia are organising summer school in bioinformatics. This course provides an introduction to the use of bioinformatics in biological research, giving you guidance for using bioinformatics in your work whilst also providing hands-on training in tools and resources appropriate to your research.

Applicants are expected to be at an early stage of using bioinformatics in their research with the need to develop their knowledge and skills further. No previous knowledge of programming is required for this course.

Applications close: 25 February 2024

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Summer school in bioinformatics

 

European Bioinformatics Institute United Kingdom in association with Elixir Estonia are organising summer school in bioinformatics. This course provides an introduction to the use of bioinformatics in biological research, giving participants guidance for using bioinformatics in their work whilst also providing hands-on training in tools and resources appropriate to their research.

Participants will initially be introduced to bioinformatics theory and practice, including best practices for undertaking bioinformatics analysis, data management, and reproducibility. To enable specific exploration of resources in their particular field of interest, participants will then be divided into focused groups to work on a project.

Participants will be required to review some pre-recorded material prior to the start of the course.

Information about the summer school

Date: 12 - 16 June 2023

Application deadline: 05 March 2023

Cost: £825.00 inclusive of four nights accommodation and catering, including dinner

Participant limit: Open application with selection 30 places

More info: https://www.ebi.ac.uk/training/events/summer-school-bioinformatics-0/

Group projects:

  • Genome variation across human populations 
  • Interpreting functional information from large scale protein structure data
  • Modelling cell signalling pathways
  • Networks and pathways
  • Reusing FAIR Bioimage data: an AI application

Who is this course for?

Applicants are expected to be at an early stage of using bioinformatics in their research with the need to develop their knowledge and skills further. No previous knowledge of programming is required for this course; group projects may give you the opportunity to learn basic programming, but participants will be supported in this by their mentors. Depending on your chosen project, an introductory programming tutorial may be given as homework prior to attending the course.

Learning outcomes

  • After this course you should be able to:
  • Discuss applications of bioinformatics in biological research
  • Browse, search, and retrieve biological data from public repositories
  • Use appropriate bioinformatics tools to explore biological data
  • Describe ways that biological data can be stored, organised and integrated