Supervised learning of high-confidence phenotypic subpopulations from single-cell data

Accurately identifying phenotype-relevant cell subsets from heterogeneous cell populations is crucial for delineating the underlying mechanisms driving biological or clinical phenotypes. Here, by deploying a learning with rejection strategy, we developed a novel supervised learning framework called...

Descripción completa

Detalles Bibliográficos
Autores principales: Ren, Tao, Chen, Canping, Danilov, Alexey V., Liu, Susan, Guan, Xiangnan, Du, Shunyi, Wu, Xiwei, Sherman, Mara H., Spellman, Paul T., Coussens, Lisa M., Adey, Andrew C., Mills, Gordon B., Wu, Ling-Yun, Xia, Zheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10055361/
https://www.ncbi.nlm.nih.gov/pubmed/36993424
http://dx.doi.org/10.1101/2023.03.23.533712

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10055361/
https://www.ncbi.nlm.nih.gov/pubmed/36993424
http://dx.doi.org/10.1101/2023.03.23.533712

Ejemplares similares