GCNCDA: A new method for predicting circRNA-disease associations based on Graph Convolutional Network Algorithm

Numerous evidences indicate that Circular RNAs (circRNAs) are widely involved in the occurrence and development of diseases. Identifying the association between circRNAs and diseases plays a crucial role in exploring the pathogenesis of complex diseases and improving the diagnosis and treatment of d...

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Veröffentlicht in:	PLoS computational biology Jg. 16; H. 5; S. e1007568
Hauptverfasser:	Wang, Lei, You, Zhu-Hong, Li, Yang-Ming, Zheng, Kai, Huang, Yu-An
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Public Library of Science 20.05.2020 Public Library of Science (PLoS)
Schlagworte:	Accuracy Algorithms Artificial neural networks Atherosclerosis Biology and Life Sciences Breast cancer Cancer Case studies Classifiers Colorectal cancer Colorectal carcinoma Competitiveness Computational biology Computer applications Datasets Deep learning Disease Diseases Ecology and Environmental Sciences Engineering and Technology Experiments Feature extraction Genetic aspects Glioma Health aspects Machine learning Medical treatment Medicine and Health Sciences Methods MicroRNAs Nervous system Pathogenesis Physical Sciences Research and Analysis Methods Risk factors RNA Similarity Social Sciences China Hong Kong China
ISSN:	1553-7358, 1553-734X, 1553-7358
Online-Zugang:	Volltext
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