AIMC Topic: RNA

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Deep generative design of RNA aptamers using structural predictions.

Nature computational science Nov 6, 2024
RNAs represent a class of programmable biomolecules capable of performing diverse biological functions. Recent studies have developed accurate RNA three-dimensional structure prediction methods, which may enable new RNAs to be designed in a structure...
Deep Learning Aptamers, Nucleotide Computational Biology RNA Computer Simulation Nucleic Acid Conformation
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GeoNet enables the accurate prediction of protein-ligand binding sites through interpretable geometric deep learning.

Structure (London, England : 1993) Nov 1, 2024
The identification of protein binding residues is essential for understanding their functions in vivo. However, it remains a computational challenge to accurately identify binding sites due to the lack of known residue binding patterns. Local residue...
Computational Biology Proteins Deep Learning Protein Binding RNA DNA Models, Molecular Ligands Binding Sites
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PseU-KeMRF: A Novel Method for Identifying RNA Pseudouridine Sites.

IEEE/ACM transactions on computational biology and bioinformatics Oct 9, 2024
Pseudouridine is a type of abundant RNA modification that is seen in many different animals and is crucial for a variety of biological functions. Accurately identifying pseudouridine sites within the RNA sequence is vital for the subsequent study of ...
Humans Algorithms Computational Biology Sequence Analysis, RNA Support Vector Machine Animals Mice Pseudouridine RNA Saccharomyces cerevisiae
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Predicting RNA sequence-structure likelihood via structure-aware deep learning.

BMC bioinformatics Sep 30, 2024
BACKGROUND: The active functionalities of RNA are recognized to be heavily dependent on the structure and sequence. Therefore, a model that can accurately evaluate a design by giving RNA sequence-structure pairs would be a valuable tool for many rese...
Sequence Analysis, RNA RNA Deep Learning Computational Biology Neural Networks, Computer Nucleic Acid Conformation
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Capture of RNA-binding proteins across mouse tissues using HARD-AP.

Nature communications Sep 28, 2024
RNA-binding proteins (RBPs) modulate all aspects of RNA metabolism, but a comprehensive picture of RBP expression across tissues is lacking. Here, we describe our development of the method we call HARD-AP that robustly retrieves RBPs and tightly asso...
Machine Learning Animals Humans Protein Binding Mice RNA-Binding Proteins RNA Binding Sites
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Wfold: A new method for predicting RNA secondary structure with deep learning.

Computers in biology and medicine Sep 27, 2024
Precise estimations of RNA secondary structures have the potential to reveal the various roles that non-coding RNAs play in regulating cellular activity. However, the mainstay of traditional RNA secondary structure prediction methods relies on thermo...
Humans Software Computational Biology Sequence Analysis, RNA Deep Learning RNA Nucleic Acid Conformation
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RNAfcg: RNA Flexibility Prediction Based on Topological Centrality and Global Features.

Journal of chemical information and modeling Sep 14, 2024
The dynamics of RNAs are related intimately to their functions. Molecular flexibility, as a starting point for understanding their dynamics, has been utilized to predict many characteristics associated with their functions. Since the experimental mea...
RNA Nucleic Acid Conformation Machine Learning Computational Biology
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A Machine Learning Method for RNA-Small Molecule Binding Preference Prediction.

Journal of chemical information and modeling Sep 12, 2024
The interaction between RNA and small molecules is crucial in various biological functions. Identifying molecules targeting RNA is essential for the inhibitor design and RNA-related studies. However, traditional methods focus on learning RNA sequence...
Nucleic Acid Conformation Small Molecule Libraries Models, Molecular RNA Machine Learning
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m5C-Seq: Machine learning-enhanced profiling of RNA 5-methylcytosine modifications.

Computers in biology and medicine Sep 3, 2024
Epigenetic modifications, particularly RNA methylation and histone alterations, play a crucial role in heredity, development, and disease. Among these, RNA 5-methylcytosine (m5C) is the most prevalent RNA modification in mammalian cells, essential fo...
Species Specificity 5-Methylcytosine Algorithms Reproducibility of Results Databases, Genetic RNA Animals Humans Machine Learning
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MultiModRLBP: A Deep Learning Approach for Multi-Modal RNA-Small Molecule Ligand Binding Sites Prediction.

IEEE journal of biomedical and health informatics Aug 6, 2024
This study aims to tackle the intricate challenge of predicting RNA-small molecule binding sites to explore the potential value in the field of RNA drug targets. To address this challenge, we propose the MultiModRLBP method, which integrates multi-mo...
Computational Biology Ligands Algorithms Small Molecule Libraries Binding Sites Nucleic Acid Conformation RNA Deep Learning
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