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Related Concept Videos

Enzyme-Linked Immunosorbent Assay01:33

Enzyme-Linked Immunosorbent Assay

In 1971, Peter Perlman and Eva Engvall developed an Enzyme-linked immunosorbent assay (ELISA or EIA). ELISA differs from western blot in that the assays are conducted in microtiter plates or in vivo rather than on an absorbent membrane.
There are many different types of ELISAs, but they all involve an antibody molecule whose constant region binds an enzyme, leaving the variable region free to bind its specific antigen.  Enzyme-substrate reaction allows the antigen to be visualized or quantified.
Cryo-electron Microscopy01:28

Cryo-electron Microscopy

Conventional electron microscopy (EM) involves dehydration, fixation, and staining of biological samples, which distorts the native state of biological molecules and results in several artifacts. Also, the high-energy electron beam damages the sample and makes it difficult to obtain high-resolution images. These issues can be addressed using cryo-EM, which uses frozen samples and gentler electron beams. The technique was developed by Jacques Dubochet, Joachim Frank, and Richard Henderson, for...

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Updated: Jun 17, 2026

The MultiBac Protein Complex Production Platform at the EMBL
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EMBL's European Bioinformatics Institute (EMBL-EBI) in 2022.

Matthew Thakur1, Alex Bateman1, Cath Brooksbank1

  • 1Data Services Teams, EMBL's European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK.

Nucleic Acids Research
|December 8, 2022
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Summary
This summary is machine-generated.

The European Bioinformatics Institute (EMBL-EBI) provides extensive, high-quality public biomolecular data. These resources are ideal for training artificial intelligence and machine learning models in life sciences research.

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Last Updated: Jun 17, 2026

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Area of Science:

  • Bioinformatics
  • Genomics
  • Life Sciences

Background:

  • The European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI) is a premier global repository for public biomolecular data.
  • EMBL-EBI is part of the European Molecular Biology Laboratory (EMBL), a leading intergovernmental life sciences organization.

Purpose of the Study:

  • To provide an overview of the services offered by EMBL-EBI data resources to the global scientific community.
  • To highlight the suitability of EMBL-EBI databases as training sets for artificial intelligence (AI), machine learning (ML), and deep learning (DL) applications.

Main Methods:

  • The abstract focuses on the characteristics of EMBL-EBI data resources, including their scale, openness, metadata richness, and curation.
  • It describes how these features facilitate AI/ML/DL applications.

Main Results:

  • EMBL-EBI's large-scale, open-access, well-curated databases are highly valuable for AI/ML/DL model training.
  • These sustainable, high-quality datasets, some collected over decades, are openly available to researchers worldwide.

Conclusions:

  • EMBL-EBI data resources are foundational for developing advanced tools and research insights across the life sciences.
  • The institute aims to continue supporting transformative research through its data provisions.