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

Fusion oncoproteins arise when a gene fuses with another gene and acquires new abilities. Such abilities can include the formation of biomolecular condensates, "droplets" of concentrated proteins, DNA ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 possible variants-more combinations than atoms in the observable universe.

Researchers led by Xian-Yang Qin at the RIKEN Center for Integrative Medical Sciences (IMS) in Japan have developed a score that predicts the risk of liver cancer. Published in the scientific journal ...

An AI approach developed by researchers from the University of Sheffield and AstraZeneca, could make it easier to design proteins needed for new treatments. In their study published in the journal ...

Researchers in the Nanoscience Center at the University of Jyväskylä, Finland, have developed a pioneering computational model that could expedite the use of nanomaterials in biomedical applications.

Machine-learning platform enables signal peptide-informed discovery of small molecules that selectively inhibit protein secretion allowing for the degradation of disease-related proteins at the point ...

A generalizable ML framework predicts protein interactions with ligand-stabilized gold nanoclusters, supporting faster design of bioimaging, sensing and drug delivery materials. (Nanowerk News) The ...