AIMC Topic: RNA

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Uncertainty Quantification and Temperature Scaling Calibration for Protein-RNA Binding Site Prediction.

Journal of chemical information and modeling Jun 2, 2025
The black-box nature of deep learning has increasingly drawn attention to the reliability and uncertainty of predictive models. Currently, several uncertainty quantification (UQ) methods have been proposed and successfully applied in the fields of mo...
Temperature Protein Binding Neural Networks, Computer Calibration Binding Sites Uncertainty RNA-Binding Proteins RNA
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Generative and predictive neural networks for the design of functional RNA molecules.

Nature communications May 4, 2025
RNA is a remarkably versatile molecule that has been engineered for applications in therapeutics, diagnostics, and in vivo information-processing systems. However, the complex relationship between the sequence, structure, and function of RNA often ne...
Thermodynamics RNA Nucleic Acid Conformation Neural Networks, Computer Algorithms
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GINClus: RNA structural motif clustering using graph isomorphism network.

NAR genomics and bioinformatics Apr 26, 2025
Ribonucleic acid (RNA) structural motif identification is a crucial step for understanding RNA structure and functionality. Due to the complexity and variations of RNA 3D structures, identifying RNA structural motifs is challenging and time-consuming...
Algorithms Deep Learning Cluster Analysis Software Nucleotide Motifs RNA Nucleic Acid Conformation
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A divide-and-conquer approach based on deep learning for long RNA secondary structure prediction: Focus on pseudoknots identification.

PloS one Apr 25, 2025
The accurate prediction of RNA secondary structure, and pseudoknots in particular, is of great importance in understanding the functions of RNAs since they give insights into their folding in three-dimensional space. However, existing approaches ofte...
RNA, Long Noncoding Nucleic Acid Conformation Software Deep Learning RNA Algorithms RNA Folding Computational Biology
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Artificial intelligence for RNA-ligand interaction prediction: advances and prospects.

Drug discovery today Apr 24, 2025
Accurate prediction of RNA-ligand interactions is vital for understanding biological processes and advancing RNA-targeted drug discovery. Given their complexity, artificial intelligence (AI) is revolutionizing the study of RNA-ligand interactions, of...
Artificial Intelligence Binding Sites Drug Discovery RNA Humans Models, Molecular Ligands
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Definer: A computational method for accurate identification of RNA pseudouridine sites based on deep learning.

PloS one Apr 24, 2025
Pseudouridine is an important modification site, which is widely present in a variety of non-coding RNAs and is involved in a variety of important biological processes. Studies have shown that pseudouridine is important in many biological functions s...
Deep Learning Mice Humans Saccharomyces cerevisiae Computational Biology Pseudouridine Animals RNA
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The prediction of RNA-small molecule binding sites in RNA structures based on geometric deep learning.

International journal of biological macromolecules Apr 21, 2025
Biological interactions between RNA and small-molecule ligands play a crucial role in determining the specific functions of RNA, such as catalysis and folding, and are essential for guiding drug design in the medical field. Accurately predicting the ...
Nucleic Acid Conformation Binding Sites RNA Ligands Small Molecule Libraries Deep Learning Computational Biology Models, Molecular
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RPI-GGCN: Prediction of RNA-Protein Interaction Based on Interpretability Gated Graph Convolution Neural Network and Co-Regularized Variational Autoencoders.

IEEE transactions on neural networks and learning systems Apr 4, 2025
RNA-protein interactions (RPIs) play an important role in several fundamental cellular physiological processes, including cell motility, chromosome replication, transcription and translation, and signaling. Predicting RPI can guide the exploration of...
Computational Biology RNA-Binding Proteins RNA Autoencoder Neural Networks, Computer Proteins Humans Algorithms
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Critical Assessment of RNA and DNA Structure Predictions via Artificial Intelligence: The Imitation Game.

Journal of chemical information and modeling Mar 30, 2025
Computational predictions of biomolecular structure via artificial intelligence (AI) based approaches, as exemplified by AlphaFold software, have the potential to model of all life's biomolecules. We performed oligonucleotide structure prediction and...
Artificial Intelligence RNA Nucleic Acid Conformation DNA Models, Molecular
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RNAmigos2: accelerated structure-based RNA virtual screening with deep graph learning.

Nature communications Mar 21, 2025
RNAs are a vast reservoir of untapped drug targets. Structure-based virtual screening (VS) identifies candidate molecules by leveraging binding site information, traditionally using molecular docking simulations. However, docking struggles to scale w...
Molecular Docking Simulation Deep Learning Nucleic Acid Conformation Binding Sites RNA Riboswitch
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