AIMC Topic: Nucleic Acid Conformation

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Modular reconfiguration of DNA origami assemblies using tile displacement.

Science robotics Apr 26, 2023
The power of natural evolution lies in the adaptability of biological organisms but is constrained by the time scale of genetics and reproduction. Engineeringartificial molecular machines should not only include adaptability as a core feature but als...
DNA Nanostructures Nucleic Acid Conformation Temperature Robotics
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RNA independent fragment partition method based on deep learning for RNA secondary structure prediction.

Scientific reports Feb 17, 2023
The non-coding RNA secondary structure largely determines its function. Hence, accuracy in structure acquisition is of great importance. Currently, this acquisition primarily relies on various computational methods. The prediction of the structures o...
Nucleic Acid Conformation Protein Structure, Secondary Computational Biology RNA Algorithms Deep Learning
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DNA Origami Nanostructure Detection and Yield Estimation Using Deep Learning.

ACS synthetic biology Jan 25, 2023
DNA origami is a milestone in DNA nanotechnology. It is robust and efficient in constructing arbitrary two- and three-dimensional nanostructures. The shape and size of origami structures vary. To characterize them, an atomic force microscope, a trans...
Nanostructures Nanotechnology Deep Learning Nucleic Acid Conformation DNA
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Research on RNA secondary structure predicting via bidirectional recurrent neural network.

BMC bioinformatics Sep 8, 2021
BACKGROUND: RNA secondary structure prediction is an important research content in the field of biological information. Predicting RNA secondary structure with pseudoknots has been proved to be an NP-hard problem. Traditional machine learning methods...
Neural Networks, Computer Algorithms RNA Nucleic Acid Conformation Protein Structure, Secondary
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Review of machine learning methods for RNA secondary structure prediction.

PLoS computational biology Aug 26, 2021
Secondary structure plays an important role in determining the function of noncoding RNAs. Hence, identifying RNA secondary structures is of great value to research. Computational prediction is a mainstream approach for predicting RNA secondary struc...
Machine Learning Computational Biology RNA Nucleic Acid Conformation
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Detecting protein and DNA/RNA structures in cryo-EM maps of intermediate resolution using deep learning.

Nature communications Apr 16, 2021
An increasing number of density maps of macromolecular structures, including proteins and DNA/RNA complexes, have been determined by cryo-electron microscopy (cryo-EM). Although lately maps at a near-atomic resolution are routinely reported, there ar...
Protein Structure, Secondary Software Computational Biology Deep Learning Models, Molecular Nucleic Acid Conformation DNA RNA Cryoelectron Microscopy
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A convolutional neural network for the prediction and forward design of ribozyme-based gene-control elements.

eLife Apr 16, 2021
Ribozyme switches are a class of RNA-encoded genetic switch that support conditional regulation of gene expression across diverse organisms. An improved elucidation of the relationships between sequence, structure, and activity can improve our capaci...
Saccharomyces cerevisiae RNA, Catalytic Ligands High-Throughput Nucleotide Sequencing Base Sequence Nucleic Acid Conformation Gene Expression Regulation Escherichia coli Structure-Activity Relationship Sequence Analysis, RNA Models, Genetic Neural Networks, Computer Computer-Aided Design Aptamers, Nucleotide Machine Learning
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ncRFP: A Novel end-to-end Method for Non-Coding RNAs Family Prediction Based on Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics Apr 6, 2021
Evidence has accumulated enough to prove non-coding RNAs (ncRNAs) play important roles in cellular biological processes and disease pathogenesis. High throughput techniques have produced a large number of ncRNAs whose function remains unknown. Since ...
Software RNA, Untranslated Sequence Analysis, RNA Nucleic Acid Conformation Deep Learning Computational Biology
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Deep learning predicts short non-coding RNA functions from only raw sequence data.

PLoS computational biology Nov 11, 2020
Small non-coding RNAs (ncRNAs) are short non-coding sequences involved in gene regulation in many biological processes and diseases. The lack of a complete comprehension of their biological functionality, especially in a genome-wide scenario, has dem...
High-Throughput Nucleotide Sequencing Nucleic Acid Conformation Computational Biology Sequence Analysis, RNA RNA, Untranslated Humans Monte Carlo Method Neural Networks, Computer Databases, Nucleic Acid Exome Sequencing Deep Learning
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Mustache: multi-scale detection of chromatin loops from Hi-C and Micro-C maps using scale-space representation.

Genome biology Sep 30, 2020
We present MUSTACHE, a new method for multi-scale detection of chromatin loops from Hi-C and Micro-C contact maps. MUSTACHE employs scale-space theory, a technical advance in computer vision, to detect blob-shaped objects in contact maps. MUSTACHE is...
Chromatin Genomics Nucleic Acid Conformation Artificial Intelligence Software
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