A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic ...

In a recent study published in the journal Nature Methods, a group of researchers developed a novel method called Ribonucleic Acid (RNA) High-Order Folding Prediction Plus (RhoFold+). This deep ...

In the rapidly advancing field of computational biology, a newly peer-reviewed review explores the transformative role of deep learning techniques in revolutionizing protein structure prediction. The ...

Physiologically Based Pharmacokinetic Model to Assess the Drug-Drug-Gene Interaction Potential of Belzutifan in Combination With Cyclin-Dependent Kinase 4/6 Inhibitors A total of 14,177 patients were ...

In order to understand currents, tides and other ocean dynamics, scientists need to accurately capture sea surface height, or ...

Researchers developed ShapKAN, a deep learning model integrated into the AI4Min-PE platform ( enabling instant prediction and ...

Lightning is one of the primary causes of transmission line trips, posing a significant threat to the safety of power grids. However, due to the complexity and sporadic nature of lightning, achieving ...

A new machine learning model developed by The George Institute for Global Health can successfully predict heart disease risk in women by analyzing mammograms. The findings were published today in ...