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RNA

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Discovery of RNA-targeted small molecules through the merging of experimental and computational technologies.

Expert opinion on drug discovery
INTRODUCTION: The field of RNA-targeted small molecules is rapidly evolving, owing to the advances in experimental and computational technologies. With the identification of several bioactive small molecules that target RNA, including the FDA-approve...

Prediction of Epstein-Barr Virus Status in Gastric Cancer Biopsy Specimens Using a Deep Learning Algorithm.

JAMA network open
IMPORTANCE: Epstein-Barr virus (EBV)-associated gastric cancer (EBV-GC) is 1 of 4 molecular subtypes of GC and is confirmed by an expensive molecular test, EBV-encoded small RNA in situ hybridization. EBV-GC has 2 histologic characteristics, lymphoid...

Machine learning for cell type classification from single nucleus RNA sequencing data.

PloS one
With the advent of single cell/nucleus RNA sequencing (sc/snRNA-seq), the field of cell phenotyping is now a data-driven exercise providing statistical evidence to support cell type/state categorization. However, the task of classifying cells into sp...

BAT-Net: An enhanced RNA Secondary Structure prediction via bidirectional GRU-based network with attention mechanism.

Computational biology and chemistry
BACKGROUND: RNA Secondary Structure (RSS) has drawn growing concern, both for their pivotal roles in RNA tertiary structures prediction and critical effect in penetrating the mechanism of functional non-coding RNA. Computational techniques that can r...

De novo prediction of RNA-protein interactions with graph neural networks.

RNA (New York, N.Y.)
RNA-binding proteins (RBPs) are key co- and post-transcriptional regulators of gene expression, playing a crucial role in many biological processes. Experimental methods like CLIP-seq have enabled the identification of transcriptome-wide RNA-protein ...

Predicting genes associated with RNA methylation pathways using machine learning.

Communications biology
RNA methylation plays an important role in functional regulation of RNAs, and has thus attracted an increasing interest in biology and drug discovery. Here, we collected and collated transcriptomic, proteomic, structural and physical interaction data...

LTPConstraint: a transfer learning based end-to-end method for RNA secondary structure prediction.

BMC bioinformatics
BACKGROUND: RNA secondary structure is very important for deciphering cell's activity and disease occurrence. The first method which was used by the academics to predict this structure is biological experiment, But this method is too expensive, causi...

Predicting RBP Binding Sites of RNA With High-Order Encoding Features and CNN-BLSTM Hybrid Model.

IEEE/ACM transactions on computational biology and bioinformatics
RNA binding protein (RBP) is extensively involved in various cellular regulatory processes through the interaction with RNAs. Capturing the RBP binding preferences is fundamental for revealing the pathogenesis of complex diseases. Many experimental d...

ZayyuNet - A Unified Deep Learning Model for the Identification of Epigenetic Modifications Using Raw Genomic Sequences.

IEEE/ACM transactions on computational biology and bioinformatics
Epigenetic modifications have a vital role in gene expression and are linked to cellular processes such as differentiation, development, and tumorigenesis. Thus, the availability of reliable and accurate methods for identifying and defining these cha...

From data to noise to data for mixing physics across temperatures with generative artificial intelligence.

Proceedings of the National Academy of Sciences of the United States of America
Using simulations or experiments performed at some set of temperatures to learn about the physics or chemistry at some other arbitrary temperature is a problem of immense practical and theoretical relevance. Here we develop a framework based on stati...