Feature selection for preserving biological trajectories in single-cell data

Single-cell technologies can readily measure the expression of thousands of molecular features from individual cells undergoing dynamic biological processes, such as cellular differentiation, immune response, and disease progression. While examining cells along a computationally ordered pseudotime o...

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Detalles Bibliográficos
Autores principales: Ranek, Jolene S., Stallaert, Wayne, Milner, Justin, Stanley, Natalie, Purvis, Jeremy E.
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/PMC10197710/
https://www.ncbi.nlm.nih.gov/pubmed/37214963
http://dx.doi.org/10.1101/2023.05.09.540043

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10197710/
https://www.ncbi.nlm.nih.gov/pubmed/37214963
http://dx.doi.org/10.1101/2023.05.09.540043

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