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. Developed by KAUST ...

Artificial intelligence (AI) is transforming how scientists understand proteins—these are working molecules that drive nearly every process in the human body, from cell growth and immune defense to ...

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 ...

Three scientists were named winners of the 2024 Nobel Prize in Chemistry for their innovations in the fields of computational protein design and structure prediction. One half of the prize was awarded ...

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 proteomics-driven approach to drug discovery improves target validation and uncovers insights into undruggable proteins, ...