Deep learning on graphs for multi-omics classification of COPD

Network approaches have successfully been used to help reveal complex mechanisms of diseases including Chronic Obstructive Pulmonary Disease (COPD). However despite recent advances, we remain limited in our ability to incorporate protein-protein interaction (PPI) network information with omics data...

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Veröffentlicht in:	PloS one 2023-04, Vol.18 (4), p.e0284563-e0284563
Hauptverfasser:	Zhuang, Yonghua, Xing, Fuyong, Ghosh, Debashis, Hobbs, Brian D, Hersh, Craig P, Banaei-Kashani, Farnoush, Bowler, Russell P, Kechris, Katerina
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Analysis Artificial neural networks Biology and Life Sciences Bone Morphogenetic Proteins Carbohydrates Chronic obstructive pulmonary disease Classification Computer and Information Sciences CXCL11 protein Deep Learning Development and progression Diagnosis DNA methylation Gene expression Glycosaminoglycans Graph neural networks Heparin Humans Identification and classification Interleukin 2 Lung diseases Lung diseases, Obstructive Machine learning Medicine and Health Sciences Methods Modelling Multiomics Neural networks Neural Networks, Computer Obstructive lung disease Pathogenesis Potassium channels (inwardly-rectifying) Prediction models Protein interaction Protein-protein interactions Proteins Proteomics Pulmonary Disease, Chronic Obstructive - genetics Research and Analysis Methods Signaling Spirometry TLR2 protein Toll-like receptors Transcriptomics
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