Protein function prediction and annotation represent critical challenges in the post‐genomic era. As high‐throughput sequencing continues to generate vast amounts of protein data, computational ...

In a recent study published in the journal Nature Machine Intelligence, researchers developed "DeepGO-SE," a method to predict gene ontology (GO) functions from protein sequences using a large, ...

University of Missouri researchers have released the world's largest collection of protein models with quality assessment—a ...

A newly developed generative AI model is helping researchers explore protein dynamics with increased speed. The deep learning system, called BioEmu, predicts the full range of conformations a protein ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20100 ...

An innovative machine learning approach has been shown to rapidly predict multiple protein configurations. A new paper presents the method that predicts the relative populations of protein ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 possible variants-more combinations than atoms in the observable universe.

Artificial intelligence has solved one of biology’s most stubborn mysteries: how proteins fold into their intricate three-dimensional shapes. But as the field shifts from prediction to application, a ...

Proteomics is the large-scale study of proteins, particularly their structures and functions. It involves the systematic identification, quantification, and analysis of the entire protein complement ...