AI Medical Compendium Topic

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RNA, Circular

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Hither-CMI: Prediction of circRNA-miRNA Interactions Based on a Hybrid Multimodal Network and Higher-Order Neighborhood Information via a Graph Convolutional Network.

Journal of chemical information and modeling
Numerous studies show that circular RNA (circRNA) functions as a sponge for microRNA (miRNA), significantly regulating gene expression by interacting with miRNA, which in turn affects the progression of human diseases. Traditional experimental approa...

Bimodal In Situ Analyzer for Circular RNA in Extracellular Vesicles Combined with Machine Learning for Accurate Gastric Cancer Detection.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Circular RNAs in extracellular vesicles (EV-circRNAs) are gaining recognition as potential biomarkers for the diagnosis of gastric cancer (GC). Most current research is focused on identifying new biomarkers and their functional significance in diseas...

Transcriptomic profiling and machine learning reveal novel RNA signatures for enhanced molecular characterization of Hashimoto's thyroiditis.

Scientific reports
While ultrasonography effectively diagnoses Hashimoto's thyroiditis (HT), exploring its transcriptomic landscape could reveal valuable insights into disease mechanisms. This study aimed to identify HT-associated RNA signatures and investigate their p...

TransRM: Weakly supervised learning of translation-enhancing N6-methyladenosine (mA) in circular RNAs.

International journal of biological macromolecules
As our understanding of Circular RNAs (circRNAs) continues to expand, accumulating evidence has demonstrated that circRNAs can interact with microRNAs and RNA-binding proteins to modulate gene expression. More importantly, a subset of circRNAs has be...

Circular RNA-Drug Association Prediction Based on Multi-Scale Convolutional Neural Networks and Adversarial Autoencoders.

International journal of molecular sciences
The prediction of circular RNA (circRNA)-drug associations plays a crucial role in understanding disease mechanisms and identifying potential therapeutic targets. Traditional methods often struggle to cope with the complexity of heterogeneous network...

Prediction of circRNA-Disease Associations via Graph Isomorphism Transformer and Dual-Stream Neural Predictor.

Biomolecules
Circular RNAs (circRNAs) have attracted increasing attention for their roles in human diseases, making the prediction of circRNA-disease associations (CDAs) a critical research area for advancing disease diagnosis and treatment. However, traditional ...

metaCDA: A Novel Framework for CircRNA-Driven Drug Discovery Utilizing Adaptive Aggregation and Meta-Knowledge Learning.

Journal of chemical information and modeling
In the emerging field of RNA drugs, circular RNA (circRNA) has attracted much attention as a novel multifunctional therapeutic target. Delving deeper into the intricate interactions between circRNA and disease is critical for driving drug discovery e...

RBPsuite 2.0: an updated RNA-protein binding site prediction suite with high coverage on species and proteins based on deep learning.

BMC biology
BACKGROUND: RNA-binding proteins (RBPs) play crucial roles in many biological processes, and computationally identifying RNA-RBP interactions provides insights into the biological mechanism of diseases associated with RBPs.

DGCLCMI: a deep graph collaboration learning method to predict circRNA-miRNA interactions.

BMC biology
BACKGROUND: Numerous studies have shown that circRNA can act as a miRNA sponge, competitively binding to miRNAs, thereby regulating gene expression and disease progression. Due to the high cost and time-consuming nature of traditional wet lab experim...

Interpretable multi-instance heterogeneous graph network learning modelling CircRNA-drug sensitivity association prediction.

BMC biology
BACKGROUND: Different expression levels of circular RNAs (circRNAs) affect the sensitivity of human cells to drugs, thus producing different responses to the therapeutic effects of drugs. Using traditional biomedical experiments to discover and confi...