‘The entire protein universe’: AI predicts shape of nearly every known protein

“From today, determining the 3D shape of almost any protein known to science will be as simple as typing in a Google search.

Researchers have used AlphaFold — the revolutionary artificial-intelligence (AI) network — to predict the structures of some 200 million proteins from 1 million species, covering nearly every known protein on the planet.

The data dump will be freely available on a database set up by DeepMind, Google’s London-based AI company that developed AlphaFold, and the European Molecular Biology Laboratory’s European Bioinformatics Institute (EMBL-EBI), an intergovernmental organization near Cambridge, UK….”

AlphaFold reveals the structure of the protein universe

“It’s been one year since we released and open sourced AlphaFold and created the AlphaFold Protein Structure Database (AlphaFold DB) to freely share this scientific knowledge with the world. Proteins are the building blocks of life, they underpin every biological process in every living thing. And, because a protein’s shape is closely linked with its function, knowing a protein’s structure unlocks a greater understanding of what it does and how it works. We hoped this groundbreaking resource would help accelerate scientific research and discovery globally, and that other teams could learn from and build on the advances we made with AlphaFold to create further breakthroughs. That hope has become a reality far quicker than we had dared to dream. Just twelve months later, AlphaFold has been accessed by more than half a million researchers and used to accelerate progress on important real-world problems ranging from plastic pollution to antibiotic resistance.

Today, I’m incredibly excited to share the next stage of this journey. In partnership with EMBL’s European Bioinformatics Institute (EMBL-EBI), we’re now releasing predicted structures for nearly all catalogued proteins known to science, which will expand the AlphaFold DB by over 200x – from nearly 1 million structures to over 200 million structures – with the potential to dramatically increase our understanding of biology….

All 200+ million structures will also be available for bulk download via Google Cloud Public Datasets, making AlphaFold even more accessible to scientists around the world….”

 

COVID-19 Data Portal

“The aim of the COVID-19 Data Portal is to facilitate data sharing and analysis, and to accelerate coronavirus research.

An unprecedented number of scientific efforts are taking place worldwide in order to help combat the new coronavirus epidemic (COVID-19). One of the biggest challenges in this fast-moving situation is to share data and findings in a coordinated way, in order to understand the disease and to develop treatments and vaccines.

To address this challenge, EMBL-EBI and partners have has set up the COVID-19 Data Portal, which will bring together relevant datasets submitted to EMBL-EBI and other major centres for biomedical data. The aim is to facilitate data sharing and analysis, and to accelerate coronavirus research.

The COVID-19 Data Portal will enable researchers to upload, access and analyse COVID-19 related reference data and specialist datasets.

The COVID-19 Data Portal will be the primary entry point into the functions of a wider project, the European COVID-19 Data Platform….
 

?enay Kafkas, Text Miner in Literature Services | European Bioinformatics Institute

“I am a text mining specialist in the Literature Services team of EMBL-EBI. My team runs and maintains the Europe PMC database, an archive of life-science literature. Our job is to make it easy for researchers to find articles and information they need. 

I contribute to the development of the text mining infrastructure of the database. My colleagues and I develop methods to annotate articles and design searches by indexing articles based on specific search fields. We are a service-oriented team and work closely with the users to make researchers’ lives easier….”