Stanford develops protein-to-DNA method enabling high-throughput protein sequencing Technique detects up to 1,000 times more ...

Large‑scale protein evolution model reveals that common ancestry, not selection or epistasis, is the dominant force limiting ...

The limitations imposed by evolution have implications for AI tools trained on existing sequences and de novo protein design ...

A team of researchers has built a new protein sequencing workflow that pairs mirror proteases with deep learning software to read peptide sequences with far greater accuracy than previous methods.

The number of known proteins is infinitely small in comparison to the universe of possible proteins, which could in theory be realized. Yet these known proteins are the only major training ground for ...

Protein sequencing presents different challenges than nucleic acid sequencing, meaning that proteomics has yet to benefit as much as genomics from the next-generation sequencing revolution. However, ...

On Wednesday, the Nobel Committee announced that it had awarded the Nobel Prize in chemistry to researchers who pioneered major breakthroughs in computational chemistry. These include two researchers ...

AI language models, used to generate human-like text to power chatbots and create content, are also revolutionizing biology ...

Various approaches to such protein redesign have drawbacks. Traditional methods include time-consuming trial and error efforts, and many models in the emerging field ...