Association prediction of CircRNAs and diseases using multi-homogeneous graphs and variational graph auto-encoder

As a non-coding RNA molecule with closed-loop structure, circular RNA (circRNA) is tissue-specific and cell-specific in expression pattern. It regulates disease development by modulating the expression of disease-related genes. Therefore, exploring the circRNA-disease relationship can reveal the mol...

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Veröffentlicht in:	Computers in biology and medicine Jg. 151; H. Pt A; S. 106289
Hauptverfasser:	Fu, Yao, Yang, Runtao, Zhang, Lina
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Elsevier Ltd 01.12.2022 Elsevier Limited
Schlagworte:	Algorithms Apoptosis Area Under Curve CircRNA-disease association Circular RNA Coders Completeness Cysts Data processing Datasets Decoding Disease Dogs Feature extraction Female Gene expression Graph neural network Graph neural networks Humans Internal Medicine Labor, Obstetric Machine learning Molecular modelling Molecular structure National libraries Neural networks Other Pathogenesis Pregnancy Proteins Random forest Ribonucleic acid RNA RNA, Circular - genetics Semantics Similarity Subject heading schemes Variational graph auto-encoder Random forest CircRNA-disease association Variational graph auto-encoder Graph neural network
ISSN:	0010-4825, 1879-0534, 1879-0534
Online-Zugang:	Volltext
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