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Integration strategies of multi-omics data for machine learning analysis

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Graphical abstract Schematic representation of the main strategies for multi-omics datasets integration. A) Early integration concatenates all omics datasets into a single matrix on which machine learning model can be… Click to show full abstract

Graphical abstract Schematic representation of the main strategies for multi-omics datasets integration. A) Early integration concatenates all omics datasets into a single matrix on which machine learning model can be applied. B) Mixed integration first independently transforms or maps each omics block into a new representation before combining them for downstream analysis. C) Intermediate integration simultaneously transforms the original datasets into common and omics-specific representations. D) Late integration analyses each omics separately and combines their final predictions. E) Hierarchical integration bases the integration of datasets on prior regulatory relationships between omics layers.

Keywords: machine learning; multi omics; integration; analysis; strategies multi

Journal Title: Computational and Structural Biotechnology Journal
Year Published: 2021

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