Through a novel combination of machine learning and atomic force microscopy, researchers in China have unveiled the molecular ...
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 ...
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, ...
The Department of Chemistry and Materials Science is looking for: ...
Fluid–structure interaction (FSI) governs how flowing water and air interact with marine structures—from wind turbines to ...
Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...
Researchers present ARES (Atomic Rotationally Equivariant Scorer) – a machine learning method that significantly improves the computational prediction of RNA structures over previous approaches. Like ...
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 ...
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 ...
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 ...
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