AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

RNA

Showing 151 to 160 of 321 articles

Clear Filters

Attention-based multi-label neural networks for integrated prediction and interpretation of twelve widely occurring RNA modifications.

Nature communications
Recent studies suggest that epi-transcriptome regulation via post-transcriptional RNA modifications is vital for all RNA types. Precise identification of RNA modification sites is essential for understanding the functions and regulatory mechanisms of...

EDLmAPred: ensemble deep learning approach for mRNA mA site prediction.

BMC bioinformatics
BACKGROUND: As a common and abundant RNA methylation modification, N6-methyladenosine (mA) is widely spread in various species' transcriptomes, and it is closely related to the occurrence and development of various life processes and diseases. Thus, ...

RNA Backbone Torsion and Pseudotorsion Angle Prediction Using Dilated Convolutional Neural Networks.

Journal of chemical information and modeling
RNA three-dimensional structure prediction has been relied on using a predicted or experimentally determined secondary structure as a restraint to reduce the conformational sampling space. However, the secondary-structure restraints are limited to pa...

Convolutional neural networks (CNNs): concepts and applications in pharmacogenomics.

Molecular diversity
Convolutional neural networks (CNNs) have been used to extract information from various datasets of different dimensions. This approach has led to accurate interpretations in several subfields of biological research, like pharmacogenomics, addressing...

RNAmining: A machine learning stand-alone and web server tool for RNA coding potential prediction.

F1000Research
Non-coding RNAs (ncRNAs) are important players in the cellular regulation of organisms from different kingdoms. One of the key steps in ncRNAs research is the ability to distinguish coding/non-coding sequences. We applied seven machine learning algor...

Detecting protein and DNA/RNA structures in cryo-EM maps of intermediate resolution using deep learning.

Nature communications
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...

High-throughput label-free detection of DNA-to-RNA transcription inhibition using brightfield microscopy and deep neural networks.

Computers in biology and medicine
Drug discovery is in constant evolution and major advances have led to the development of in vitro high-throughput technologies, facilitating the rapid assessment of cellular phenotypes. One such phenotype is immunogenic cell death, which occurs part...

A novel end-to-end method to predict RNA secondary structure profile based on bidirectional LSTM and residual neural network.

BMC bioinformatics
BACKGROUND: Studies have shown that RNA secondary structure, a planar structure formed by paired bases, plays diverse vital roles in fundamental life activities and complex diseases. RNA secondary structure profile can record whether each base is pai...

DNN-m6A: A Cross-Species Method for Identifying RNA N6-Methyladenosine Sites Based on Deep Neural Network with Multi-Information Fusion.

Genes
As a prevalent existing post-transcriptional modification of RNA, N6-methyladenosine (m6A) plays a crucial role in various biological processes. To better radically reveal its regulatory mechanism and provide new insights for drug design, the accurat...

Predicting dynamic cellular protein-RNA interactions by deep learning using in vivo RNA structures.

Cell research
Interactions with RNA-binding proteins (RBPs) are integral to RNA function and cellular regulation, and dynamically reflect specific cellular conditions. However, presently available tools for predicting RBP-RNA interactions employ RNA sequence and/o...