# ProtBERT Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/protbert
> Markdown URL: https://aitinkerers.org/technologies/protbert.md
> Technology record last updated: 2026-03-19T07:00:27Z
> Generated: 2026-10-24T21:10:00Z

A self-supervised transformer model trained on 217 million protein sequences to predict secondary structure and subcellular localization.

Developed by researchers at the Technical University of Munich, ProtBERT adapts the BERT architecture to the language of life by training on the UniRef100 dataset (217 million sequences). It bypasses the need for costly Multiple Sequence Alignments (MSA) by learning intrinsic biophysical properties directly from raw amino acid strings. The model achieves state-of-the-art performance on benchmarks like NetSurfP-2.0 for secondary structure prediction and DeepLoc for localization, providing a high-throughput alternative to traditional bioinformatics pipelines.

- Official technology site: https://github.com/agemaghsoudi/ProtBert
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Apple Protein Vision and LLMs for Bioinformatics](https://la.aitinkerers.org/talks/rsvp_fiy7Fw_wI9s)

- Event context: June 25th - LA AI Tinkerers Meetup & Demos — 2024-06-26 — Los Angeles
- Public talk page: https://la.aitinkerers.org/talks/rsvp_fiy7Fw_wI9s

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