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 ...

This fully updated volume explores a wide array of new and state-of-the-art tools and resources for protein function prediction. Beginning with in-depth overviews of essential underlying 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. A new artificial ...

At AACR 2026, researchers discussed the promise and challenges of bringing AI-powered tools into cancer research and clinical ...

Advances in generative AI, automation, and high‑throughput experimentation are rapidly changing protein engineering, enabling faster design, stability prediction, and functional optimization. New ...

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 ...

This review examines how high-throughput proteomics is expanding precision medicine by improving biomarker discovery, disease ...

Recent advances in high-throughput proteomics enable the measurement of thousands of proteins simultaneously, offering ...

Protein engineering is a field primed for artificial intelligence research. Each protein is made up of amino acids; to ...