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, ...

A new artificial intelligence (AI) tool that draws logical inferences about the function of unknown proteins promises to help scientists unravel the inner workings of the cell. Developed by KAUST ...

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

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 ...

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 ...

A new artificial intelligence (AI) tool that draws logical inferences about the function of unknown proteins promises to help scientists unravel the inner workings of the cell. A new artificial ...

Researchers present BioEmu – a new AI model that rapidly and accurately predicts the full range of shapes a protein can adopt, offering a faster, cheaper alternative to traditional molecular ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

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