Application of Deep Learning on Single-Cell RNA-sequencing Data Analysis: A Review. (arXiv:2210.05677v1 [q-bio.GN])

Single-cell RNA-sequencing (scRNA-seq) has become a routinely used technique
to quantify the gene expression profile of thousands of single cells
simultaneously. Analysis of scRNA-seq data plays an important role in the study
of cell states and phenotypes, and has helped elucidate biological processes,
such as those occurring during development of complex organisms and improved
our understanding of disease states, such as cancer, diabetes, and COVID, among
others. Deep learning, a recent advance of artificial intelligence that has
been used to …

analysis application arxiv bio data data analysis deep learning review rna sequencing