AIMC Topic: Nucleic Acid Conformation

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Predict the degree of secondary structures of the encoding sequences in DNA storage by deep learning model.

Scientific reports Jul 1, 2025
DNA storage has been widely considered as a promising alternative for exponentially growing data. However, the inherent complex secondary structures severely compromise the processes of synthesis, PCR amplification, and sequencing, interfering with r...
Nucleic Acid Conformation Deep Learning DNA
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Comprehensive datasets for RNA design, machine learning, and beyond.

Scientific reports Jul 1, 2025
RNA molecules are essential in regulating biological processes such as gene expression, cellular differentiation, and development. Accurately predicting RNA secondary structures and designing sequences that fold into specific configurations remain si...
RNA Nucleic Acid Conformation Machine Learning Algorithms Computational Biology
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RiNALMo: general-purpose RNA language models can generalize well on structure prediction tasks.

Nature communications Jul 1, 2025
While RNA has recently been recognized as an interesting small-molecule drug target, many challenges remain to be addressed before we take full advantage of it. This emphasizes the necessity to improve our understanding of its structures and function...
Software Deep Learning RNA Nucleic Acid Conformation Computational Biology Sequence Analysis, RNA RNA, Untranslated
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Quantifying complexity in DNA structures with high resolution Atomic Force Microscopy.

Nature communications Jul 1, 2025
DNA topology is essential for regulating cellular processes and maintaining genome stability, yet it is challenging to quantify due to the size and complexity of topologically constrained DNA molecules. By combining high-resolution Atomic Force Micro...
DNA Replication Escherichia coli Microscopy, Atomic Force DNA Plasmids Animals Nucleic Acid Conformation Xenopus laevis
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Deep generalizable prediction of RNA secondary structure via base pair motif energy.

Nature communications Jul 1, 2025
Deep learning methods have demonstrated great performance for RNA secondary structure prediction. However, generalizability is a common unsolved issue on unseen out-of-distribution RNA families, which hinders further improvement of the accuracy and r...
Computational Biology RNA Nucleotide Motifs Deep Learning Thermodynamics Nucleic Acid Conformation Base Pairing
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Melting Profile of DNA in Crowded Solution: Model-Based Study.

International journal of molecular sciences May 31, 2025
Recent advances in molecular dynamics (MD) simulations and the introduction of artificial intelligence (AI) have resulted in a significant increase in accuracy for structure prediction. However, the cell is a highly crowded environment consisting of ...
DNA Molecular Dynamics Simulation Nucleic Acid Conformation Nucleic Acid Denaturation Solutions
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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...
Nucleic Acid Conformation Thermodynamics Algorithms RNA Neural Networks, Computer
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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...
Nucleic Acid Conformation Nucleotide Motifs Algorithms Software Deep Learning Cluster Analysis RNA
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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 Folding Computational Biology Algorithms RNA Software RNA, Long Noncoding Deep Learning Nucleic Acid Conformation
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Identification of potential riboswitch elements in Homo sapiens mRNA 5'UTR sequences using positive-unlabeled machine learning.

PloS one Apr 24, 2025
Riboswitches are a class of noncoding RNA structures that interact with target ligands to cause a conformational change that can then execute some regulatory purpose within the cell. Riboswitches are ubiquitous and well characterized in bacteria and ...
5' Untranslated Regions Machine Learning Humans RNA, Messenger Nucleic Acid Conformation Ligands Riboswitch Base Sequence
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