PhenoGMM: Gaussian mixture modeling of cytometry data quantifies changes inmicrobial community structure

Rubbens, P.; Props, R.; Kerckhof, F.-M.; Boon, N.; Waegeman, W.

doi:/10.1128/msphere.00530-20

IMIS - Marine Research Groups

[ report an error in this record ]

basket (0): add | show

PhenoGMM: Gaussian mixture modeling of cytometry data quantifies changes inmicrobial community structure

Rubbens, P.; Props, R.; Kerckhof, F.-M.; Boon, N.; Waegeman, W. (2021). PhenoGMM: Gaussian mixture modeling of cytometry data quantifies changes inmicrobial community structure. mSphere 6(1): e00530-20. https://dx.doi.org/10.1128/msphere.00530-20

In: mSphere. American Society for Microbiology: Washington. e-ISSN 2379-5042, more

Available in	Authors
VLIZ: Open access 370898 [ download pdf ]

Author keywords

diversity, fingerprint, flow cytometry, machine learning, microbial communities, mixture model

Authors		Top
Rubbens, P., more Props, R., more Kerckhof, F.-M., more	Boon, N., more Waegeman, W., more

All data in the Integrated Marine Information System (IMIS) is subject to the VLIZ privacy policy

Top | Authors

You are here

IMIS - Marine Research Groups