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Machine Intelligence in Single-Cell Data Analysis: Advances and New Challenges
2021
Frontiers in Genetics
The rapid development of single-cell technologies allows for dissecting cellular heterogeneity at different omics layers with an unprecedented resolution. In-dep analysis of cellular heterogeneity will boost our understanding of complex biological systems or processes, including cancer, immune system and chronic diseases, thereby providing valuable insights for clinical and translational research. In this review, we will focus on the application of machine learning methods in single-cell
doi:10.3389/fgene.2021.655536
pmid:34135939
pmcid:PMC8203333
fatcat:tp5v7gtdwnezjfrfef45ctidye