Biophysical informatics reveals distinctive phenotypic signatures and functional diversity of single-cell lineages

MOTIVATION: In this work, we present an analytical method for quantifying both single-cell morphologies and cell network topologies of tumor cell populations and use it to predict 3D cell behavior. RESULTS: We utilized a supervised deep learning approach to perform instance segmentation on label-fre...

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Detalles Bibliográficos
Autores principales: Chan, Trevor J, Zhang, Xingjian, Mak, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825265/
https://www.ncbi.nlm.nih.gov/pubmed/36610710
http://dx.doi.org/10.1093/bioinformatics/btac833

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825265/
https://www.ncbi.nlm.nih.gov/pubmed/36610710
http://dx.doi.org/10.1093/bioinformatics/btac833

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