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 novel bioinformatics approach for classifying proteins according to similarity of function, rather than of sequence, is described in the April 12 PNAS. Albert Y. Lau and Daniel I. Chasman of ...

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 ...

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 ...

Researchers recently published findings that could lay the groundwork for applying quantum computing methods to protein structure prediction. Researchers from Cleveland Clinic and IBM recently ...

The 2024 Nobel Prize in Chemistry is for computational protein design and structure prediction. David Baker, Demis Hassabis and John M. Jumper took home the prize for their work using artificial ...

The 2024 Nobel Prize in Chemistry goes to researchers who cracked the code for proteins’ structures, the Royal Swedish Academy of Sciences announced today (Oct 9). David Baker, a biochemist at the ...

Predicting which proteins bind to each other, or protein-protein interactions, has been a challenge for methods based in computational biology. One of the reasons is primarily due to the vast ...

A new artificial intelligence model can predict how different proteins may bind to DNA. A new artificial intelligence model developed by USC researchers and published in Nature Methods can predict how ...

Intrinsically disordered proteins (IDPs) make up about 30 percent of our proteome. They are important to many fundamental aspects of biology and disrupted in disease. Since they lack a stable shape, ...