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DRLiPS: a novel method for prediction of druggable RNA-small molecule binding pockets using machine learning.

Nucleic acids research Mar 20, 2025
Ribonucleic Acid (RNA) is the central conduit for information transfer in the cell. Identifying potential RNA targets in disease conditions is a challenging task, given the vast repertoire of functional non-coding RNAs in a human cell. A potential dr...
Humans Algorithms Molecular Docking Simulation RNA Machine Learning Software Binding Sites Ligands Nucleic Acid Conformation
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BAMBI integrates biostatistical and artificial intelligence methods to improve RNA biomarker discovery.

Briefings in bioinformatics Mar 4, 2025
RNA biomarkers enable early and precise disease diagnosis, monitoring, and prognosis, facilitating personalized medicine and targeted therapeutic strategies. However, identification of RNA biomarkers is hindered by the challenge of analyzing relative...
RNA Biostatistics Machine Learning Gene Expression Profiling Software Computational Biology Humans Algorithms Artificial Intelligence Biomarkers Biomarkers, Tumor
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DRAG: design RNAs as hierarchical graphs with reinforcement learning.

Briefings in bioinformatics Mar 4, 2025
The rapid development of RNA vaccines and therapeutics puts forward intensive requirements on the sequence design of RNAs. RNA sequence design, or RNA inverse folding, aims to generate RNA sequences that can fold into specific target structures. To d...
Neural Networks, Computer Computational Biology Machine Learning RNA Algorithms Nucleic Acid Conformation
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The Evolution of Nucleic Acid-Based Diagnosis Methods from the (pre-)CRISPR to CRISPR era and the Associated Machine/Deep Learning Approaches in Relevant RNA Design.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2025
Nucleic acid tests (NATs) are considered as gold standard in molecular diagnosis. To meet the demand for onsite, point-of-care, specific and sensitive, trace and genotype detection of pathogens and pathogenic variants, various types of NATs have been...
Deep Learning CRISPR-Cas Systems Nucleic Acid Amplification Techniques Molecular Diagnostic Techniques Humans Clustered Regularly Interspaced Short Palindromic Repeats RNA Machine Learning
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Generative Modeling of RNA Sequence Families with Restricted Boltzmann Machines.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2025
In this chapter, we discuss the potential application of Restricted Boltzmann machines (RBM) to model sequence families of structured RNA molecules. RBMs are a simple two-layer machine learning model able to capture intricate sequence dependencies in...
Models, Molecular RNA Software Riboswitch Algorithms Nucleic Acid Conformation Machine Learning Computational Biology
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gRNAde: A Geometric Deep Learning Pipeline for 3D RNA Inverse Design.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2025
Fundamental to the diverse biological functions of RNA are its 3D structure and conformational flexibility, which enable single sequences to adopt a variety of distinct 3D states. Currently, computational RNA design tasks are often posed as inverse p...
Nucleic Acid Conformation RNA, Catalytic Computational Biology Models, Molecular Neural Networks, Computer RNA Software Deep Learning
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Machine Learning for RNA Design: LEARNA.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2025
Machine learning algorithms, and in particular deep learning approaches, have recently garnered attention in the field of molecular biology due to remarkable results. In this chapter, we describe machine learning approaches specifically developed for...
RNA Nucleic Acid Conformation Deep Learning Computational Biology Software Algorithms Machine Learning
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DeepRSMA: a cross-fusion-based deep learning method for RNA-small molecule binding affinity prediction.

Bioinformatics (Oxford, England) Nov 28, 2024
MOTIVATION: RNA is implicated in numerous aberrant cellular functions and disease progressions, highlighting the crucial importance of RNA-targeted drugs. To accelerate the discovery of such drugs, it is essential to develop an effective computationa...
Small Molecule Libraries Computational Biology RNA Software Deep Learning
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Nmix: a hybrid deep learning model for precise prediction of 2'-O-methylation sites based on multi-feature fusion and ensemble learning.

Briefings in bioinformatics Sep 23, 2024
RNA 2'-O-methylation (Nm) is a crucial post-transcriptional modification with significant biological implications. However, experimental identification of Nm sites is challenging and resource-intensive. While multiple computational tools have been de...
Deep Learning Computational Biology Bayes Theorem Neural Networks, Computer Software RNA Processing, Post-Transcriptional RNA Humans Methylation
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Comparative analysis of RNA 3D structure prediction methods: towards enhanced modeling of RNA-ligand interactions.

Nucleic acids research Jul 22, 2024
Accurate RNA structure models are crucial for designing small molecule ligands that modulate their functions. This study assesses six standalone RNA 3D structure prediction methods-DeepFoldRNA, RhoFold, BRiQ, FARFAR2, SimRNA and Vfold2, excluding web...
Ligands Models, Molecular Nucleic Acid Conformation Machine Learning Binding Sites RNA Folding RNA Software
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