(14) Predicting the presence and abundance of bacterial taxa in environmental communities through flow cytometric fingerprintingJ. Heyse, F. Schattenberg, P. Rubbens, S. Müller, W. Waegeman, N. Boon and R. Props (2021) MSYSTEMS. 6, e00551-21. |
(13) PhenoGMM: Gaussian mixture modelling of cytometry data quantifies changes in microbial community structureP. Rubbens, R. Props, F.-M. Kerckhof, N. Boon and W. Waegeman(2021) MSPHERE. 6, e00530-20. |
(12) Cytometric fingerprints of gut microbiota predict Crohn's disease state P. Rubbens, R. Props, F.-M. Kerckhof, N. Boon and W. Waegeman(2021) THE ISME JOURNAL. 15, 354-358. |
(11) Discriminating bacterial phenotypes at the population and single-cell level: a comparison of flow cytometry and Raman spectroscopy fingerprintingC. García-Timermans, P. Rubbens, J. Heyse, F.-M. Kerckhof, R. Props, A. G. Skirtach, W. Waegeman and N. Boon(2020) CYTOMETRY: PART A. 97, 713-726. |
(10) Fast pathogen identification using single-cell Matrix-Assisted Laser Desorption/Ionization-Aerosol Time-of-Flight mass spectrometry data and deep learning methodsC. Papagiannopoulou, R. Parchen, P. Rubbens and W. Waegeman(2020) ANALYTICAL CHEMISTRY. 92, 7523-7531. |
(9) Randomized lasso links microbial taxa with aquatic functional groups inferred from flow cytometryP. Rubbens, M. Schmidt, R. Props, B. Biddanda, N. Boon, W. Waegeman and V. Denef(2019) MSYSTEMS. 4, 00093-19. |
(8) Learning single-cell distances from cytometry dataB. Nguyen, P. Rubbens, F.-M. Kerckhof, N. Boon, B. De Baets and W. Waegeman(2019) CYTOMETRY PART A. 95, 782-791. |
(7) Cyt-Geist: Current and Future Challenges in Cytometry: Reports of the CYTO 2018 Conference WorkshopsK. Czechowska, J. Lannigan, L. Wang, J. Arcidiacono, T.M. Ashhurst, R.M. Barnard, S. Bauer, C. Bispo, D.L. Bonilla, R.R. Brinkman, M. Cabanski, H. Chang, L. Chakrabarti, G. Chojnowski, B. Cotleur, H. Degheidy, G.V. Dela Cruz, S. Eck, J. Elliott, R. Errington, A. Filby, D. Gagnon, R. Gardner, C. Green, M. Gregory, C.J. Groves, C. Hall, F. Hammes, M. Hedrick, R. Hoffman, J. Icha, J. Ivaska, D.C. Jenner, D. Jones, F-M. Kerckhof, C. Kukat, D. Lanham, S. Leavesley, M. Lee, S. Lin-Gibson, V. Litwin, Y. Liu, J. Molloy, J.S. Moore, S. Müller, J. Nedbal, R. Niesner, N. Nitta, B. Ohlsson-Wilhelm, N.E. Paul, S. Perfetto, Z. Portat, R. Props, S. Radtke, R. Rayanki, A. Rieger, S. Rogers, P. Rubbens, R. Salomon, M. Schiemann, J. Sharpe, S.U. Sonder, J.J. Stewart, Y. Sun, H. Ulrich, G. Van Isterdael, A. Vitaliti, C. van Vreden, M. Weber, J. Zimmermann, G. Vacca, P. Wallace and A. Tárnok(2019) CYTOMETRY PART A. 95, 598-644. |
(6) Coculturing bacteria leads to reduced phenotypic heterogeneitiesJ. Heyse, B. Buysschaert, R. Props, P. Rubbens, A. Skirtach, W. Waegeman and N. Boon(2019) APPLIED AND ENVIRONMENTAL MICROBIOLOGY. 85, e02814-18. |
(5) Detection of microbial disturbances in a drinking water microbial community through continuous acquisition and advanced analysis of flow cytometry dataR. Props, P. Rubbens, M. Besmer, B. Buysschaert, J. Sigrist, H. Weilenmann, W. Waegeman, N. Boon and F. Hammes(2018) WATER RESEARCH. 145, 73-82. |
(4) Label-free Raman characterization of bacteria calls for standardized proceduresC. García-Timermans, P. Rubbens, F.-M. Kerckhof, B. Buysschaert, D. Khalenkow, W. Waegeman, A. Skirtach and N. Boon(2018) JOURNAL OF MICROBIOLOGICAL METHODS. 151, 69-75. |
(3) Stripping flow cytometry: how many detectors do we need for bacterial identification?P. Rubbens, R. Props, C. Garcia-Timmermans, N. Boon and W. Waegeman(2017) CYTOMETRY PART A. 91, 1184-1191. |
(2) Flow cytometric single-cell identification of populations in synthetic bacterial communitiesP. Rubbens, R. Props, N. Boon and W. Waegeman(2017) PLOS ONE. 12, e0169754. |
(1) Absolute quantification of microbial taxon abundancesR. Props, F-M. Kerckhof, P. Rubbens, J. De Vrieze, E. Hernandez Sanabria, W. Waegeman, P. Monsieurs, F. Hammes and N. Boon(2017) THE ISME JOURNAL. 11, 584-587. |