Rubbens P - Search Results

1

Coculturing Bacteria Leads to Reduced Phenotypic Heterogeneities.

Heyse J, Buysschaert B, Props R, Rubbens P, Skirtach AG, Waegeman W, Boon N. Heyse J, et al. Among authors: rubbens p. Appl Environ Microbiol. 2019 Apr 4;85(8):e02814-18. doi: 10.1128/AEM.02814-18. Print 2019 Apr 15. Appl Environ Microbiol. 2019. PMID: 30796063 Free PMC article.

2

Discriminating Bacterial Phenotypes at the Population and Single-Cell Level: A Comparison of Flow Cytometry and Raman Spectroscopy Fingerprinting.

García-Timermans C, Rubbens P, Heyse J, Kerckhof FM, Props R, Skirtach AG, Waegeman W, Boon N. García-Timermans C, et al. Among authors: rubbens p. Cytometry A. 2020 Jul;97(7):713-726. doi: 10.1002/cyto.a.23952. Epub 2019 Dec 30. Cytometry A. 2020. PMID: 31889414 Free article.

3

Absolute quantification of microbial taxon abundances.

Props R, Kerckhof FM, Rubbens P, De Vrieze J, Hernandez Sanabria E, Waegeman W, Monsieurs P, Hammes F, Boon N. Props R, et al. Among authors: rubbens p. ISME J. 2017 Feb;11(2):584-587. doi: 10.1038/ismej.2016.117. Epub 2016 Sep 9. ISME J. 2017. PMID: 27612291 Free PMC article.

4

Flow Cytometric Single-Cell Identification of Populations in Synthetic Bacterial Communities.

Rubbens P, Props R, Boon N, Waegeman W. Rubbens P, et al. PLoS One. 2017 Jan 25;12(1):e0169754. doi: 10.1371/journal.pone.0169754. eCollection 2017. PLoS One. 2017. PMID: 28122063 Free PMC article.

5

Learning Single-Cell Distances from Cytometry Data.

Nguyen B, Rubbens P, Kerckhof FM, Boon N, De Baets B, Waegeman W. Nguyen B, et al. Among authors: rubbens p. Cytometry A. 2019 Jul;95(7):782-791. doi: 10.1002/cyto.a.23792. Epub 2019 May 17. Cytometry A. 2019. PMID: 31099963 Free article.

6

Randomized Lasso Links Microbial Taxa with Aquatic Functional Groups Inferred from Flow Cytometry.

Rubbens P, Schmidt ML, Props R, Biddanda BA, Boon N, Waegeman W, Denef VJ. Rubbens P, et al. mSystems. 2019 Sep 10;4(5):e00093-19. doi: 10.1128/mSystems.00093-19. mSystems. 2019. PMID: 31506260 Free PMC article.

7

PhenoGMM: Gaussian Mixture Modeling of Cytometry Data Quantifies Changes in Microbial Community Structure.

Rubbens P, Props R, Kerckhof FM, Boon N, Waegeman W. Rubbens P, et al. mSphere. 2021 Feb 3;6(1):e00530-20. doi: 10.1128/mSphere.00530-20. mSphere. 2021. PMID: 33536320 Free PMC article.

8

Predicting the Presence and Abundance of Bacterial Taxa in Environmental Communities through Flow Cytometric Fingerprinting.

Heyse J, Schattenberg F, Rubbens P, Müller S, Waegeman W, Boon N, Props R. Heyse J, et al. Among authors: rubbens p. mSystems. 2021 Oct 26;6(5):e0055121. doi: 10.1128/mSystems.00551-21. Epub 2021 Sep 21. mSystems. 2021. PMID: 34546074 Free PMC article.

9

Stripping flow cytometry: How many detectors do we need for bacterial identification?

Rubbens P, Props R, Garcia-Timermans C, Boon N, Waegeman W. Rubbens P, et al. Cytometry A. 2017 Dec;91(12):1184-1191. doi: 10.1002/cyto.a.23284. Epub 2017 Nov 22. Cytometry A. 2017. PMID: 29165907 Free article.

10

Label-free Raman characterization of bacteria calls for standardized procedures.

García-Timermans C, Rubbens P, Kerckhof FM, Buysschaert B, Khalenkow D, Waegeman W, Skirtach AG, Boon N. García-Timermans C, et al. Among authors: rubbens p. J Microbiol Methods. 2018 Aug;151:69-75. doi: 10.1016/j.mimet.2018.05.027. Epub 2018 Jun 14. J Microbiol Methods. 2018. PMID: 29909167

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