Translating single-cell genomics into cell types

Type
Article
Authors
Tegner, Jesper cc
KAUST Department
Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
Biological and Environmental Science and Engineering (BESE) Division
Bioscience Program
Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Date
2023-01-12
Permanent link to this record
http://hdl.handle.net/10754/687443

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Abstract
Machine translation of languages can now automatically detect different cell types from single-cell transcriptomic data. Such a feat opens the prospect of dissecting complex clinical samples such as heterogenous tumours at scale.
Citation
Tegner, J. N. (2023). Translating single-cell genomics into cell types. Nature Machine Intelligence, 5(1), 11–12. https://doi.org/10.1038/s42256-022-00600-6
Sponsors
J.N.T. acknowledge support from the King Abdullah University of Science and Technology.
Publisher
Springer Science and Business Media LLC
Journal
NATURE MACHINE INTELLIGENCE
DOI
10.1038/s42256-022-00600-6
Additional Links
https://www.nature.com/articles/s42256-022-00600-6
Collections
Articles; Biological and Environmental Science and Engineering (BESE) Division; Bioscience Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division