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 ...
A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...
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 ...
One of the shared, fundamental goals of most chemistry researchers is the need to predict a molecule's properties, such as its boiling or melting point. Once researchers can pinpoint that prediction, ...
Researchers developed ShapKAN, a deep learning model integrated into the AI4Min-PE platform ( enabling instant prediction and ...
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 ...
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