Pathology Portal

How to interpret AlphaFold structures

Not yet rated

This webinar will introduce AlphaFold system for prediction and interpretation of protein structures. This webinar is designed for experimental biologists who wish to understand the strengths and limitations of AlphaFold and use the models to guide their experimental studies.

In this webinar we will provide an overview for the AlphaFold method and statistics that can be used to understand the reliability of the models. We will also introduce the AlphaFold Database, which provides hundreds of thousands of ready-made models across the tree of life, as well as highlight the AlphaFold Open SourceandColab notebooks that can be used to generate structures of sequences not yet available within the AlphaFold Database.

We will conclude by demonstrating a range of use cases followed by a question and answer session with all the presenters.

Who is this course for?

This webinar is suitable for lab-based andcomputational researchers with an interest instructural biology.

Outcomes

By the end of the webinar you will be able to:

  • Explain basic principles of how AlphaFold 2.0 works
  • Discuss how to interpret the results of AlphaFold
  • Identify where to find AlphaFold models at EMBL-EBI
  • Explore how to easily create AlphaFold models using Open source and Google Colab
  • Alex Bateman
    EMBL-EBI
  • Sameer Velankar
    EMBL-EBI
  • Kathryn Tunyasuvakool
    DeepMind
  • Sergey Ovchinnikov
    Harvard University
  • Pedro Beltrao
    EMBL-EBI
  • Bálint Mészáros
    EMBL

Resource details

Contributed by: Pathology Portal
Authored by: Alex Bateman, The European Molecular Biology Laboratory-European Bioinformatics Institute's (EMBL-EBI).
Sameer Velankar, The European Molecular Biology Laboratory-European Bioinformatics Institute's (EMBL-EBI).
Pedro Beltrao, The European Molecular Biology Laboratory-European Bioinformatics Institute's (EMBL-EBI).
Bálint Mészáros, The European Molecular Biology Laboratory-European Bioinformatics Institute's (EMBL-EBI).
Kathryn Tunyasuvakool, DeepMind, The European Molecular Biology Laboratory-European Bioinformatics Institute's (EMBL-EBI).
Sergey Ovchinnikov, Harvard University, The European Molecular Biology Laboratory-European Bioinformatics Institute's (EMBL-EBI).
M Prahladan, Pathology portal
Licence: Creative commons: Attribution-NonCommercial 4.0 International More information on licences
First contributed: 02 June 2024
Audience access level: General user

Ratings

0 ratings

Not yet rated
5 star
0%
4 star
0%
3 star
0%
2 star
0%
1 star
0%
Report an issue with this resource

You may report a resource, for example, if there is an issue with copyright infringement, breach of personal data, factual inaccuracies, typing errors or safety concerns. The type of issue will determine whether the resource is immediately removed from the platform or if the contributor is asked to make amendments. You can report a resource from the resource information page or by contacting the Learning Hub support team.

You can contact the Learning Hub support team by completing the support form or if you have a general enquiry you can email enquiries@learninghub.nhs.uk.