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, ...

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 ...

University of Michigan researchers have developed a new, more efficient technique for predicting protein properties, according to a study published in March. The study used a combination of ...

Add Yahoo as a preferred source to see more of our stories on Google. New AI model predicts mRNA protein output, aiding drug and vaccine design by targeting specific cells. (CREDIT: Science Photo ...

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 ...

Researchers from the University of Illinois at Urbana-Champaign and the University of California-Davis (UC Davis) are combining in vivo experimentation with computation for highly accurate prediction ...

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 ...

Researchers developed a new machine learning method that, given a relevant amino acid sequence, can automatically predict the location of a protein in any human cell line down to the single-cell level ...

Announcing a new publication for Acta Materia Medica journal. Proteins are essential macromolecules that perform functions according to their conformational dynamics. Studying the conformational ...