An AI approach developed by researchers from the University of Sheffield and AstraZeneca, could make it easier to design proteins needed for new treatments. Inverse protein folding is a critical ...
CGSchNet, a fast machine-learned model, simulates proteins with high accuracy, enabling drug discovery and protein engineering for cancer treatment. Operating significantly faster than traditional all ...
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.
Their overview highlights innovative methods based on B-factor analysis, ancestral sequence reconstruction (ASR), and machine learning (ML), providing tools to design enzymes that withstand high ...
The small size of nanoparticles is associated with several unique properties that mediate a profound impact on the development of many technological fields, including medicine. The nanoparticles in ...
Scientists have used deep learning to design new proteins that bind to complexes involving other small molecules like hormones or drugs, opening up a world of possibilities in the computational design ...
A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
The 2024 Nobel Prize in chemistry recognized Demis Hassabis, John Jumper and David Baker for using machine learning to tackle one of biology’s biggest challenges: predicting the 3D shape of proteins ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results