Protein scientists could improve reproducibility and coordination across the field by rallying around a small, shared set of ...

An international team led by Einstein Professor Cecilia Clementi in the Department of Physics at Freie Universität Berlin introduces a breakthrough in protein simulation. The study, published in the ...

Inside the race to turn one of cell biology’s least understood processes into a new foundation for drug development and ...

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 ...

Machine learning (ML) is transforming protein structure prediction. Algorithms can predict 3D structures from amino acid sequences, surpassing slower, more expensive traditional methods. ML-based ...

The 2024 Nobel Prize in chemistry recognized Demis Hassabis, John Jumper and David Baker for using machine learning to tackle ...

In a new study published in Nature titled, “Custom CRISPR-Cas9 PAM variants via scalable engineering and machine learning,” researchers from Massachusetts General Hospital (MGH) and Harvard Medical ...

It has long been thought that protein function and stability are highly sensitive to changes in the composition of the internal structures, or protein cores. However, a large-scale experiment probing ...

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 ...

The "Protein Engineering for Pharmaceutical Biotechnology Training Course (Jan 21st - Jan 22nd, 2026)" training has been added to ResearchAndMarkets.com's offering. Enhance your knowledge in protein ...