Uploaded March 2023 | Updated September 2026, 2 weeks ago
In this episode of ResearchBytes, you’ll learn how Google Research is working together with the European Bioinformatics Institute at the European Molecular Biology Laboratory to predict the function of proteins. Andreea Gane from the Brain Team at Google Research shares insights on ProtNLM, which can predict a short functional description from a protein’s amino acid sequence. Predictions from ProtNLM are now used to label millions of protein sequences that previously had no description in the institute’s database.
Resources:
Read the ProtNLM preprint → storage.googleapis.com/brain-genomics-public/research/proteins/protnlm/uniprot_2022_04/protnlm_preprint_draft.pdf
Read the ProtNLM help page on the UniProt website → uniprot.org/help/ProtNLM
See ProtNLM predictions on the UniProt website → uniprot.org/uniprotkb?query=(source:google)
Explore the Colab notebook that provides evidence for ProtNLM predictions → colab.research.google.com/github/google-research/google-research/blob/master/protnlm/protnlm_evidencer_uniprot_2023_01.ipynb
Explore the curation example shown in the video, starting with the UniProt entry containing the ProtNLM prediction. → uniprot.org/uniprotkb/D2GX75/entry#names_and_taxonomy
Chapters:
0:00 - Intro
0:50 - What’s the challenge?
3:16 - What did we do?
3:40 - How did we do it?
5:00 - What did we observe?
6:10 - What’s next?
We thank our collaborators at EMBL-EBI, and in particular Dr. Elena Speretta for assembling the curation example included in the video, and for the careful work in evaluating predictions.
ebi.ac.uk/people/person/elena-speretta
Watch more episodes of ResearchBytes → https://goo.gle/ResearchBytes
Subscribe to the Google Research Channel → https://goo.gle/GoogleResearch
#ResearchBytes
In this episode of ResearchBytes, you’ll learn how Google Research is working together with the European Bioinformatics Institute at the European Molecular Biology Laboratory to predict the function of proteins. Andreea Gane from the Brain Team at Google Research shares insights on ProtNLM, which can predict a short functional description from a protein’s amino acid sequence. Predictions from ProtNLM are now used to label millions of protein sequences that previously had no description in the institute’s database.
Resources:
Read the ProtNLM preprint → storage.googleapis.com/brain-genomics-public/research/proteins/protnlm/uniprot_2022_04/protnlm_preprint_draft.pdf
Read the ProtNLM help page on the UniProt website → uniprot.org/help/ProtNLM
See ProtNLM predictions on the UniProt website → uniprot.org/uniprotkb?query=(source:google)
Explore the Colab notebook that provides evidence for ProtNLM predictions → colab.research.google.com/github/google-research/google-research/blob/master/protnlm/protnlm_evidencer_uniprot_2023_01.ipynb
Explore the curation example shown in the video, starting with the UniProt entry containing the ProtNLM prediction. → uniprot.org/uniprotkb/D2GX75/entry#names_and_taxonomy
Chapters:
0:00 - Intro
0:50 - What’s the challenge?
3:16 - What did we do?
3:40 - How did we do it?
5:00 - What did we observe?
6:10 - What’s next?
We thank our collaborators at EMBL-EBI, and in particular Dr. Elena Speretta for assembling the curation example included in the video, and for the careful work in evaluating predictions.
ebi.ac.uk/people/person/elena-speretta
Watch more episodes of ResearchBytes → https://goo.gle/ResearchBytes
Subscribe to the Google Research Channel → https://goo.gle/GoogleResearch
#ResearchBytes










