Deep learning shapes single-cell data analysis

Deep learning has tremendous potential in single-cell data analyses, but numerous challenges and possible new developments remain to be explored. In this commentary, we consider the progress, limitations, best practices and outlook of adapting deep learning methods for analysing single-cell data.

Detalles Bibliográficos
Autores principales: Ma, Qin, Xu, Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Comment
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8864973/
https://www.ncbi.nlm.nih.gov/pubmed/35197610
http://dx.doi.org/10.1038/s41580-022-00466-x
Descripción
Sumario:Deep learning has tremendous potential in single-cell data analyses, but numerous challenges and possible new developments remain to be explored. In this commentary, we consider the progress, limitations, best practices and outlook of adapting deep learning methods for analysing single-cell data.

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