Decoding cell identity with multi-scale explainable deep learning

Abstract excerpt

Cells are the fundamental structural and functional units of life. Studying the definition and composition of different cell types can help us understand the complex mechanisms underlying biological diversity and functionality. The increasing volume of extensive single-cell omics data makes it possible to provide detailed characterisations of cell types. Recently, there has been a rise in deep learning-based appro...

Topics

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• Algorithms
• Bees
• Cluster Analysis
• Gene Expression Regulation
• Neonatal Respiratory Health Research
• Neural Networks, Computer
• Phenotype
• Single-cell and spatial transcriptomics

Identifiers and source

Literature Corpus work

2951960a-0204-5276-9ec2-3bdccbe08dae

DOI

10.1101/2024.02.05.578922