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Deep learning applications in single-cell omics data analysis
[article]
2021
bioRxiv
pre-print
Deep learning (DL) is a branch of machine learning (ML) capable of extracting high-level features from raw inputs in multiple stages. Compared to traditional ML, DL models have provided significant improvements across a range of domains and applications. Single-cell (SC) omics are often high-dimensional, sparse, and complex, making DL techniques ideal for analyzing and processing such data. We examine DL applications in a variety of single-cell omics (genomics, transcriptomics, proteomics,
doi:10.1101/2021.11.26.470166
fatcat:3bmpecoza5dedbmwm62jwhfm4e