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flowPeaks: a fast unsupervised clustering for flow cytometry data via K-means and density peak finding
Motivation: For flow cytometry data, there are two common approaches to the unsupervised clustering problem: one is based on the finite mixture model and the other on spatial exploration of the histograms. The former is computationally slow and has difficulty to identify clusters of irregular shapes...
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| Autors principals: | , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Oxford University Press
2012
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3400953/ https://ncbi.nlm.nih.gov/pubmed/22595209 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/bts300 |
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