AI Medical Compendium Topic

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RNA, Circular

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CRBPDL: Identification of circRNA-RBP interaction sites using an ensemble neural network approach.

PLoS computational biology
Circular RNAs (circRNAs) are non-coding RNAs with a special circular structure produced formed by the reverse splicing mechanism. Increasing evidence shows that circular RNAs can directly bind to RNA-binding proteins (RBP) and play an important role ...

circRNA-binding protein site prediction based on multi-view deep learning, subspace learning and multi-view classifier.

Briefings in bioinformatics
Circular RNAs (circRNAs) generally bind to RNA-binding proteins (RBPs) to play an important role in the regulation of autoimmune diseases. Thus, it is crucial to study the binding sites of RBPs on circRNAs. Although many methods, including traditiona...

GMNN2CD: identification of circRNA-disease associations based on variational inference and graph Markov neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: With the analysis of the characteristic and function of circular RNAs (circRNAs), people have realized that they play a critical role in the diseases. Exploring the relationship between circRNAs and diseases is of far-reaching significanc...

Prediction of circRNA-Disease Associations Based on the Combination of Multi-Head Graph Attention Network and Graph Convolutional Network.

Biomolecules
Circular RNAs (circRNAs) are covalently closed single-stranded RNA molecules, which have many biological functions. Previous experiments have shown that circRNAs are involved in numerous biological processes, especially regulatory functions. It has a...

A web server for identifying circRNA-RBP variable-length binding sites based on stacked generalization ensemble deep learning network.

Methods (San Diego, Calif.)
Circular RNA (circRNA) can exert biological functions by interacting with RNA-binding protein (RBP), and some deep learning-based methods have been developed to predict RBP binding sites on circRNA. However, most of these methods identify circRNA-RBP...

A machine learning framework based on multi-source feature fusion for circRNA-disease association prediction.

Briefings in bioinformatics
Circular RNAs (circRNAs) are involved in the regulatory mechanisms of multiple complex diseases, and the identification of their associations is critical to the diagnosis and treatment of diseases. In recent years, many computational methods have bee...

MNMDCDA: prediction of circRNA-disease associations by learning mixed neighborhood information from multiple distances.

Briefings in bioinformatics
Emerging evidence suggests that circular RNA (circRNA) is an important regulator of a variety of pathological processes and serves as a promising biomarker for many complex human diseases. Nevertheless, there are relatively few known circRNA-disease ...

Deep learning models for disease-associated circRNA prediction: a review.

Briefings in bioinformatics
Emerging evidence indicates that circular RNAs (circRNAs) can provide new insights and potential therapeutic targets for disease diagnosis and treatment. However, traditional biological experiments are expensive and time-consuming. Recently, deep lea...

Convolution Neural Networks Using Deep Matrix Factorization for Predicting Circrna-Disease Association.

IEEE/ACM transactions on computational biology and bioinformatics
CircRNAs have a stable structure, which gives them a higher tolerance to nucleases. Therefore, the properties of circular RNAs are beneficial in disease diagnosis. However, there are few known associations between circRNAs and disease. Biological exp...

Collaborative deep learning improves disease-related circRNA prediction based on multi-source functional information.

Briefings in bioinformatics
Emerging studies have shown that circular RNAs (circRNAs) are involved in a variety of biological processes and play a key role in disease diagnosing, treating and inferring. Although many methods, including traditional machine learning and deep lear...