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 ...

Machine learning has emerged as a transformative tool in quantum chemistry, offering unprecedented speed and scalability while retaining near–ab initio accuracy. At its core, modern approaches employ ...

A new trick for modeling molecules with quantum accuracy takes a step toward revealing the equation at the center of a popular simulation approach, which is used in fundamental chemistry and materials ...

Machine learning is changing the front end of drug discovery, where researchers decide which targets to pursue and which molecules deserve costly laboratory work. Its deeper test lies further ...

Making high-performance proteins for medicines or consumer products can take trial after trial of tweaks, experiments and fine-tuning. A new machine learning framework squeezes all that into a single ...

In a recent review article published in the journal Annual Review of Analytical Chemistry, researchers highlighted the transformative role of machine learning (ML) in advancing mass spectrometry (MS) ...

A team of researchers at Rice University and Baylor College of Medicine has developed a new strategy for identifying hazardous pollutants in soil, even ones that have never been isolated or studied in ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...