Automatic Classification of Cellular Expression by Nonlinear Stochastic Embedding (ACCENSE)

Mass cytometry enables an unprecedented number of parameters to be measured in individual cells at a high throughput, but the large dimensionality of the resulting data severely limits approaches relying on manual “gating.” Clustering cells based on phenotypic similarity comes at a loss of single-ce...

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Bibliographic Details
Main Authors: Shekhar, Karthik, Brodin, Petter, Davis, Mark M., Chakraborty, Arup K.
Format: Artigo
Language:Inglês
Published: National Academy of Sciences 2014
Subjects:
Biological Sciences
Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC3890841/
https://ncbi.nlm.nih.gov/pubmed/24344260
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1073/pnas.1321405111
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