Proteins spontaneously fold into intricate three-dimensional shapes which are key to nearly every biological process. But the complexity of protein shapes makes them difficult to study. Recently, ...

A new machine learning tool developed at Princeton will enable researchers to sift through trillions of design options to predict which metal organic framework will be useful in laboratories or ...

Researchers present ARES (Atomic Rotationally Equivariant Scorer) – a machine learning method that significantly improves the computational prediction of RNA structures over previous approaches. Like ...

Princeton researchers have developed a new tool to speed the discovery of advanced materials known as metal organic ...

A new machine-learning approach assesses the accuracy of structural models of RNA molecules. From a training set of known RNA structures, the algorithm learns the characteristic features of RNA, such ...

Imagine having a super-powered lens that uncovers hidden secrets of ultra-thin materials used in our gadgets. Research led by University of Florida engineering professor Megan Butala enables a novel ...

Please provide your email address to receive an email when new articles are posted on . A machine learning model may aid the detection and classification of tertiary lymphoid structures associated ...

Managing real-time data is crucial for technologies that help computers learn and make decisions, a field known as machine learning. In simple terms, machine learning teaches computers to find ...

If nonliving materials can produce rich, organized mixtures of organic molecules, then the traditional signs we use to ...

Fluid–structure interaction (FSI) governs how flowing water and air interact with marine structures—from wind turbines to ...