Although deep learning–based image recognition technology is rapidly advancing, it still remains difficult to clearly explain ...

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 ...

Researchers have developed a deep-learning model, called PepFlow, that can predict all possible shapes of peptides -- chains of amino acids that are shorter than proteins, but perform similar ...

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 ...

This review provides an overview of traditional and modern methods for protein structure prediction and their characteristics and introduces the groundbreaking network features of the AlphaFold family ...

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...

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A research team, led by Professor Jimin Lee and Professor Eisung Yoon in the Department of Nuclear Engineering at UNIST, has unveiled a deep learning–based approach that significantly accelerates the ...

Although deep learning–based image recognition technology is rapidly advancing, it still remains difficult to clearly explain the criteria AI uses ...

Research combining deep learning methodologies with Analytic Hierarchy Process establishes comprehensive frameworks for data security risk assessment, achieving systematic evaluation and preventive ...