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A semi-supervised approach for the integration of multi-omics data based on transformer multi-head self-attention mechanism and graph convolutional networks

22 Jan 2024

Abstract excerpt

BACKGROUND AND OBJECTIVES: Comprehensive analysis of multi-omics data is crucial for accurately formulating effective treatment plans for complex diseases. Supervised ensemble methods have gained popularity in recent years for multi-omics data analysis. However, existing research based on supervised learning algorithms often fails to fully harness the information from unlabeled nodes and overlooks the latent...

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PMID: 38254021
DOI: 10.1186/s12864-024-09985-7

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