Course at EMBL-EBI

Protein function prediction with machine learning and interactive analytics

Do you want to learn how to develop models to predict protein function? Do you want analyse and exploit the growing volume of biological data? Do you want to develop basic skills in novel machine learning approaches and big data technologies?

This workshop explores how to conduct functional annotation of proteins through machine learning (ML) approaches. Participants will gain an insight into existing public protein data resources; and how novel approaches can be used to analyse and explore these data to gain new understanding of protein function. The workshop will introduce Apache Spark and Apache Zeppelin; technologies for fast data processing and integrating analytics respectively.

Who is this course for?

This workshop is aimed at researchers and bioinformaticians from across industry and academia who are looking to leverage machine learning approaches in protein function prediction. It will guide participants through the use of big data to build analytical workflows on publically-available biological data.

Participants will require prior experience in the use of the command line interface and confidence in a programming language to fully benefit from the workshop. Please contact us if you have any questions about the course's suitability before you apply.

What will I learn?

Learning outcomes

After this course you should be able to:

  • Search and locate protein data of interest
  • Conduct interactive analytics and data transformation using machine learning approaches
  • Create simple analytical workflows using publically-available data
  • Discern new biological insights about protein function
  • Develop models for predicting protein function

Course content

The workshop will cover the following topics:


Tom Hancocks
Rabie Saidi
Hermann Zellner
This course has ended

29 - 30 May 2019
European Bioinformatics Institute
United Kingdom
Marina Pujol

  • Tom Hancocks
  • Rabie Saidi

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