Decoding tumor microenvironments through artificial tumor transcriptomes
1Department of Computational Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA.
Abstract:
In this issue of Cancer Cell, Zaitsev et al. (2022) present a machine-learning-based approach, trained from millions of artificial transcriptomes with admixed cell populations, for reconstructing tumor microenvironments (TMEs). The high accuracy of this approach, demonstrated through extensive validation, enables systematic investigation of TMEs in both research and clinical settings.
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