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Integrating temporal single-cell gene expression modalities for trajectory inference and disease prediction

BACKGROUND: Current methods for analyzing single-cell datasets have relied primarily on static gene expression measurements to characterize the molecular state of individual cells. However, capturing temporal changes in cell state is crucial for the interpretation of dynamic phenotypes such as the c...

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Detalles Bibliográficos
Autores principales: Ranek, Jolene S., Stanley, Natalie, Purvis, Jeremy E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9442962/
https://www.ncbi.nlm.nih.gov/pubmed/36064614
http://dx.doi.org/10.1186/s13059-022-02749-0

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