AIMC Topic: RNA

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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...
Software Deep Learning Humans RNA Nucleic Acid Conformation Computational Biology Sequence Analysis, RNA
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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...
Machine Learning Nucleic Acid Conformation Computational Biology RNA
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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...
Models, Molecular Machine Learning Nucleic Acid Conformation RNA Small Molecule Libraries
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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...
Algorithms RNA Reproducibility of Results Species Specificity 5-Methylcytosine Animals Humans Databases, Genetic 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...
Small Molecule Libraries RNA Ligands Nucleic Acid Conformation Binding Sites Deep Learning Computational Biology Algorithms
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m5c-iDeep: 5-Methylcytosine sites identification through deep learning.

Methods (San Diego, Calif.) Jul 31, 2024
5-Methylcytosine (m5c) is a modified cytosine base which is formed as the result of addition of methyl group added at position 5 of carbon. This modification is one of the most common PTM that used to occur in almost all types of RNA. The conventiona...
RNA 5-Methylcytosine Deep Learning Humans Computational Biology Computer Simulation
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pyRBDome: a comprehensive computational platform for enhancing RNA-binding proteome data.

Life science alliance Jul 30, 2024
High-throughput proteomics approaches have revolutionised the identification of RNA-binding proteins (RBPome) and RNA-binding sequences (RBDome) across organisms. Yet, the extent of noise, including false positives, associated with these methodologie...
Computational Biology RNA-Binding Proteins Software Protein Binding Humans Databases, Protein Proteomics Binding Sites Machine Learning RNA Proteome
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Exploring the roles of RNAs in chromatin architecture using deep learning.

Nature communications Jul 29, 2024
Recent studies have highlighted the impact of both transcription and transcripts on 3D genome organization, particularly its dynamics. Here, we propose a deep learning framework, called AkitaR, that leverages both genome sequences and genome-wide RNA...
RNA, Long Noncoding DNA RNA Chromatin Deep Learning Cell Line Humans
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Moss-m7G: A Motif-Based Interpretable Deep Learning Method for RNA N7-Methlguanosine Site Prediction.

Journal of chemical information and modeling Jul 16, 2024
N-7methylguanosine (m7G) modification plays a crucial role in various biological processes and is closely associated with the development and progression of many cancers. Accurate identification of m7G modification sites is essential for understandin...
Nucleotide Motifs Guanosine Deep Learning RNA
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Self-supervised learning for characterising histomorphological diversity and spatial RNA expression prediction across 23 human tissue types.

Nature communications Jul 13, 2024
As vast histological archives are digitised, there is a pressing need to be able to associate specific tissue substructures and incident pathology to disease outcomes without arduous annotation. Here, we learn self-supervised representations using a ...
Organ Specificity Humans Gene Expression Profiling Supervised Machine Learning Image Processing, Computer-Assisted RNA
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