Recent advances in computational biology have revolutionised the field of protein structure and function prediction. Traditionally, determining the three‐dimensional architecture of a protein from its ...

With MassiveFold, scientists have unlocked AlphaFold's full potential, making high-confidence protein predictions faster and more accessible, fueling breakthroughs in biology and drug discovery. Brief ...

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 ...

Google DeepMind’s work with AlphaFold has been nothing short of a miracle, but it is computationally expensive. With that in mind, Apple researchers set off to develop an alternative method to use AI ...

Artificial intelligence (AI) is reshaping the scientific landscape, offering fantastic solutions to some of the most pressing global challenges. From combating climate change to transforming ...

The scientists constructed a machine learning algorithm based on AlphaFold2 (a protein structure predictor whose developers, John Jumper and Demis Hassabis, shared the Nobel Prize in Chemistry with ...

A research group led by Gian Gaetano Tartaglia, Principal Investigator at the Italian Institute of Technology (IIT), developed a machine-learning algorithm to study the behavior of proteins within ...

A machine-learning algorithm to study the behavior of proteins within cells and to predict their ability to trigger neurodegenerative diseases such as Amyotrophic Lateral Sclerosis (ALS), Parkinson's, ...