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Nucleic Acids

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Protein-protein and protein-nucleic acid binding site prediction via interpretable hierarchical geometric deep learning.

GigaScience
Identification of protein-protein and protein-nucleic acid binding sites provides insights into biological processes related to protein functions and technical guidance for disease diagnosis and drug design. However, accurate predictions by computati...

Accurate structure prediction of biomolecular interactions with AlphaFold 3.

Nature
The introduction of AlphaFold 2 has spurred a revolution in modelling the structure of proteins and their interactions, enabling a huge range of applications in protein modelling and design. Here we describe our AlphaFold 3 model with a substantially...

SOFB is a comprehensive ensemble deep learning approach for elucidating and characterizing protein-nucleic-acid-binding residues.

Communications biology
Proteins and nucleic-acids are essential components of living organisms that interact in critical cellular processes. Accurate prediction of nucleic acid-binding residues in proteins can contribute to a better understanding of protein function. Howev...

NucleoFind: a deep-learning network for interpreting nucleic acid electron density.

Nucleic acids research
Nucleic acid electron density interpretation after phasing by molecular replacement or other methods remains a difficult problem for computer programs to deal with. Programs tend to rely on time-consuming and computationally exhaustive searches to re...

AI-empowered visualization of nucleic acid testing.

Life sciences
AIMS: The visualization of nucleic acid testing (NAT) results plays a critical role in diagnosing and monitoring infectious and genetic diseases. The review aims to review the current status of AI-based NAT result visualization. It systematically int...

Machine Learning-Assisted, Dual-Channel CRISPR/Cas12a Biosensor-In-Microdroplet for Amplification-Free Nucleic Acid Detection for Food Authenticity Testing.

ACS nano
The development of novel detection technology for meat species authenticity is imperative. Here, we developed a machine learning-supported, dual-channel biosensor-in-microdroplet platform for meat species authenticity detection named CC-drop (RISPR/C...

Deciphering Protein Secondary Structures and Nucleic Acids in Cryo-EM Maps Using Deep Learning.

Journal of chemical information and modeling
With the resolution revolution of cryo-electron microscopy (cryo-EM) and the rapid development of image processing technology, cryo-EM has become an indispensable experimental method for determining the three-dimensional structures of biological macr...

[Intelligent design of nucleic acid elements in biomanufacturing].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
Nucleic acid elements are essential functional sequences that play critical roles in regulating gene expression, optimizing pathways, and enabling gene editing to enhance the production of target products in biomanufacturing. Therefore, the design an...

Machine-Learning Framework to Predict the Performance of Lipid Nanoparticles for Nucleic Acid Delivery.

ACS applied bio materials
Lipid nanoparticles (LNPs) are highly effective carriers for gene therapies, including mRNA and siRNA delivery, due to their ability to transport nucleic acids across biological membranes, low cytotoxicity, improved pharmacokinetics, and scalability....