AIMC Topic: RNA

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RBPsuite 2.0: an updated RNA-protein binding site prediction suite with high coverage on species and proteins based on deep learning.

BMC biology Mar 11, 2025
BACKGROUND: RNA-binding proteins (RBPs) play crucial roles in many biological processes, and computationally identifying RNA-RBP interactions provides insights into the biological mechanism of diseases associated with RBPs.
RNA, Circular RNA Binding Sites Software Deep Learning Computational Biology RNA-Binding Proteins Humans
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DHUpredET: A comparative computational approach for identification of dihydrouridine modification sites in RNA sequence.

Analytical biochemistry Mar 6, 2025
Laboratory-based detection of D sites is laborious and expensive. In this study, we developed effective machine learning models employing efficient feature encoding methods to identify D sites. Initially, we explored various state-of-the-art feature ...
Machine Learning RNA Base Sequence Uridine Computational Biology Sequence Analysis, RNA
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RNA structure prediction using deep learning - A comprehensive review.

Computers in biology and medicine Feb 20, 2025
In computational biology, accurate RNA structure prediction offers several benefits, including facilitating a better understanding of RNA functions and RNA-based drug design. Implementing deep learning techniques for RNA structure prediction has led ...
Humans Nucleic Acid Conformation Deep Learning Computational Biology RNA
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RNA-protein interaction prediction using network-guided deep learning.

Communications biology Feb 16, 2025
Accurate computational determination of RNA-protein interactions remains challenging, particularly when encountering unknown RNAs and proteins. The limited number of RNAs and their flexibility constrained the effectiveness of the deep-learning models...
RNA Deep Learning Computational Biology RNA-Binding Proteins COVID-19 RNA, Viral SARS-CoV-2 Humans Neural Networks, Computer
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Identifying RNA-small Molecule Binding Sites Using Geometric Deep Learning with Language Models.

Journal of molecular biology Feb 15, 2025
RNAs are emerging as promising therapeutic targets, yet identifying small molecules that bind to them remains a significant challenge in drug discovery. This underscores the crucial role of computational modeling in predicting RNA-small molecule bind...
Models, Molecular RNA Binding Sites Drug Discovery Deep Learning Nucleic Acid Conformation Small Molecule Libraries Computational Biology
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Deep learning for RNA structure prediction.

Current opinion in structural biology Feb 10, 2025
Predicting RNA structures from sequences with computational approaches is of vital importance in RNA biology considering the high costs of experimental determination. AI methods have revolutionized this field in recent years, enabling RNA structure p...
Computational Biology RNA Deep Learning Nucleic Acid Conformation
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ERNIE-ac4C: A Novel Deep Learning Model for Effectively Predicting N4-acetylcytidine Sites.

Journal of molecular biology Feb 1, 2025
RNA modifications are known to play a critical role in gene regulation and cellular processes. Specifically, N4-acetylcytidine (ac4C) modification has emerged as a significant marker involved in mRNA translation efficiency, stability, and various dis...
Neural Networks, Computer Deep Learning Computational Biology Humans RNA Processing, Post-Transcriptional RNA Cytidine
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ZeRPI: A graph neural network model for zero-shot prediction of RNA-protein interactions.

Methods (San Diego, Calif.) Jan 30, 2025
RNA-protein interactions are crucial for biological functions across multiple levels. RNA binding proteins (RBPs) intricately engage in diverse biological processes through specific RNA molecule interactions. Previous studies have revealed the indisp...
Computational Biology RNA-Binding Proteins Algorithms RNA Humans Protein Binding Neural Networks, Computer Graph Neural Networks Machine Learning
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The prediction of RNA-small-molecule ligand binding affinity based on geometric deep learning.

Computational biology and chemistry Jan 29, 2025
Small molecule-targeted RNA is an emerging technology that plays a pivotal role in drug discovery and inhibitor design, with widespread applications in disease treatment. Consequently, predicting RNA-small-molecule ligand interactions is crucial. Wit...
Ligands Small Molecule Libraries Deep Learning Binding Sites RNA
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Enhanced Sampling Simulations of RNA-Peptide Binding Using Deep Learning Collective Variables.

Journal of chemical information and modeling Jan 7, 2025
Enhanced sampling (ES) simulations of biomolecular recognition, such as binding small molecules to proteins and nucleic acid targets, protein-protein association, and protein-nucleic acid interactions, have gained significant attention in the simulat...
RNA Nucleic Acid Conformation RNA, Viral Molecular Dynamics Simulation Peptides Deep Learning Protein Binding
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