Rapid detection of microbiota cell type diversity using machine-learned classification of flow cytometry data

The study of complex microbial communities typically entails high-throughput sequencing and downstream bioinformatics analyses. Here we expand and accelerate microbiota analysis by enabling cell type diversity quantification from multidimensional flow cytometry data using a supervised machine learni...

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Detalles Bibliográficos
Autores principales: Özel Duygan, Birge D., Hadadi, Noushin, Babu, Ambrin Farizah, Seyfried, Markus, van der Meer, Jan R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363847/
https://www.ncbi.nlm.nih.gov/pubmed/32669688
http://dx.doi.org/10.1038/s42003-020-1106-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363847/
https://www.ncbi.nlm.nih.gov/pubmed/32669688
http://dx.doi.org/10.1038/s42003-020-1106-y

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