{"personrec":{"StatusID":1,"PersStatus":null,"Status":"Valid","PersID":38084,"PersName":"Rubbens, Peter","PublicFlag":1,"CheckedFlag":0,"Surname":"Rubbens","Firstname":"Peter","Initials":"P.","AddressedAs":null,"Function":null,"DateLastModified":{"date":"2024-06-04 01:34:08.417000","timezone_type":1,"timezone":"+00:00"},"PersTitle":null,"PersStatusID":null,"AbstractEnglish":null,"AbstractOtherLang":null,"AbstractLangCode":null,"AbstractLangID":null,"AutID":266533,"ND":"2019-10-14","UD":"2019-10-14","ORCID":"0000-0001-5595-4758"},"loaninfo":null,"pictures":[{"pic_id":140669,"Typ":3,"Descr":"Person on image","imis_show":1,"preferred":1,"URL":"\/imis?page=image&pic=140669","ext":"jpg","url":"https:\/\/images.vliz.be\/thumbs\/140669_peter-rubbens.jpg"}],"institutes":null,"pastins":[{"instituterec":{"InsID":36,"FullOrigName":"Flanders Marine Institute","Acronym":"VLIZ","Function":"Postdoctoral researcher","BeginDay":15,"BeginMonth":10,"BeginYear":2019,"EndDay":24,"EndMonth":9,"EndYear":2021,"Notes":null,"Line1":null,"Line2":null,"Line3":null,"Line4":null,"Phone":null,"GSM":null,"Email":null,"FullStandardName":"Vlaams Instituut voor de Zee"},"parent":null,"institutes":null,"references":null,"conferences":null,"datasets":null,"persons":null,"pastpers":null,"subpers":null,"projects":null,"urls":null,"pictures":null,"published":null,"affrefs":null,"collections":null,"thesterms":null,"taxterms":null,"geoterms":null,"thestermsFRIS":null,"nXtins":null,"previns":null,"spcols":null,"resmessage":"no id specified","complete":0,"participantrec":null,"peerrevs":null,"urlmaps":null}],"projects":[],"datasets":null,"references":{"A1":[{"BRefID":365920,"RR":"<b>Rubbens, P.; Brodie, S.; Cordier, T.; Barcellos, D.D.; Devos, P.; Fernandes-Salvador, J.A.; Fincham, J.I.; Gomes, A.; Handegard, N.O.; Howell, K.; Jamet, C.; Kartveit, K.H.; Moustahfid, H.; Parcerisas, C.; Politikos, D.; Sauz\u00e8de, R.; Sokolova, M.; Uusitalo, L.; Van den Bulcke, L.; van Helmond, A.T.M.; Watson, J.T.; Welch, H.; Beltran-Perez, O.; Chaffron, S.; Greenberg, D.S.; K\u00fchn, B.; Kiko, R.; Lo, M.; Lopes, R.M.; M\u00f6ller, K.O.; Michaels, W.; Pala, A.; Romagnan, J.-B.; Schuchert, P.; Seydi, V.; Villasante, S.; Malde, K.; Irisson, J.-O.<\/b> (2023). Machine learning in marine ecology: An overview of techniques and applications. <i>ICES J. Mar. Sci.\/J. Cons. int. Explor. Mer 80(7)<\/i>: 1829-1853. <a href=\"https:\/\/dx.doi.org\/10.1093\/icesjms\/fsad100\" target=\"_blank\">https:\/\/dx.doi.org\/10.1093\/icesjms\/fsad100<\/a>","AutID":417610,"MonDate":null,"AnaDate":2023,"PeerRev":1,"outputType":"1_A1","OpenAcc":1},{"BRefID":348868,"RR":"<b>Heyse, J.; Schattenberg, F.; Rubbens, P.; M\u00fcller, S.; Waegeman, W.; Boon, N.; Props, R.<\/b> (2021). Predicting the presence and abundance of bacterial taxa in environmental communities through flow cytometric fingerprinting. <i>mSystems 6(5)<\/i>: e00551-21. <a href=\"https:\/\/dx.doi.org\/10.1128\/msystems.00551-21\" target=\"_blank\">https:\/\/dx.doi.org\/10.1128\/msystems.00551-21<\/a>","AutID":417610,"MonDate":null,"AnaDate":2021,"PeerRev":1,"outputType":"1_A1","OpenAcc":1},{"BRefID":332287,"RR":"<b>Rubbens, P.; Props, R.; Kerckhof, F.-M.; Boon, N.; Waegeman, W.<\/b> (2021). Cytometric fingerprints of gut microbiota predict Crohn\u2019s disease state. <i>ISME J. 15(1)<\/i>: 354-358. <a href=\"https:\/\/dx.doi.org\/10.1038\/s41396-020-00762-4\" target=\"_blank\">https:\/\/dx.doi.org\/10.1038\/s41396-020-00762-4<\/a>","AutID":499295,"MonDate":null,"AnaDate":2021,"PeerRev":1,"outputType":"1_A1","OpenAcc":0},{"BRefID":348873,"RR":"<b>Rubbens, P.; Props, R.; Kerckhof, F.-M.; Boon, N.; Waegeman, W.<\/b> (2021). PhenoGMM: Gaussian mixture modeling of cytometry data quantifies changes inmicrobial community structure. <i>mSphere 6(1)<\/i>: e00530-20. <a href=\"https:\/\/dx.doi.org\/10.1128\/msphere.00530-20\" target=\"_blank\">https:\/\/dx.doi.org\/10.1128\/msphere.00530-20<\/a>","AutID":499295,"MonDate":null,"AnaDate":2021,"PeerRev":1,"outputType":"1_A1","OpenAcc":1},{"BRefID":334823,"RR":"<b>Rubbens, P.; Props, R.<\/b> (2021). Computational analysis of microbial flow cytometry data. <i>mSystems 6(1)<\/i>: e00895-20. <a href=\"https:\/\/dx.doi.org\/10.1128\/msystems.00895-20\" target=\"_blank\">https:\/\/dx.doi.org\/10.1128\/msystems.00895-20<\/a>","AutID":417610,"MonDate":null,"AnaDate":2021,"PeerRev":1,"outputType":"1_A1","OpenAcc":1},{"BRefID":321078,"RR":"<b>Garc\u00eda-Timermans, C.; Rubbens, P.; Heyse, J.; Kerckhof, F.-M.; Props, R.; Skirtach, A.G.; Waegeman, W.; Boon, N.<\/b> (2020). Discriminating bacterial phenotypes at the population and single\u2010cell level: a comparison of flow cytometry and Raman spectroscopy fingerprinting. <i>Cytometry A 97(7)<\/i>: 713-726. <a href=\"https:\/\/dx.doi.org\/10.1002\/cyto.a.23952\" target=\"_blank\">https:\/\/dx.doi.org\/10.1002\/cyto.a.23952<\/a>","AutID":499295,"MonDate":null,"AnaDate":2020,"PeerRev":1,"outputType":"1_A1","OpenAcc":0},{"BRefID":324685,"RR":"<b>Papagiannopoulou, C.; Parchen, R.; Rubbens, P.; Waegeman, W.<\/b> (2020). Fast pathogen identification using single-cell matrix-assisted laser desorption\/ionization-aerosol time-of-flight mass spectrometry data and deep learning methods. <i>Anal. Chem. 92(11)<\/i>: 7523-7531. <a href=\"https:\/\/dx.doi.org\/10.1021\/acs.analchem.9b05806\" target=\"_blank\">https:\/\/dx.doi.org\/10.1021\/acs.analchem.9b05806<\/a>","AutID":417610,"MonDate":null,"AnaDate":2020,"PeerRev":1,"outputType":"1_A1","OpenAcc":1},{"BRefID":321910,"RR":"<b>Czechowska, Kamila; Lannigan, Joanne; Wang, Lili; Arcidiacono, Judith; Ashhurst, Thomas M.; Barnard, Ruth M.; Bauer, Steven; Bispo, Cl\u00e1udia; Bonilla, Diana L.; Brinkman, Ryan R.; Cabanski, Maciej; Chang, Hyun\u2010Dong; Chakrabarti, Lina; Chojnowski, Grace; Cotleur, Bunny; Degheidy, Heba; Dela Cruz, Gelo V.; Eck, Steven; Elliott, John; Errington, Rachel; Filby, Andy; Gagnon, Dominic; Gardner, Rui; Green, Cherie; Gregory, Michael; Groves, Christopher J.; Hall, Christopher; Hammes, Frederik; Hedrick, Michael; Hoffman, Robert; Icha, Jaroslav; Ivaska, Johanna; Jenner, Dominic C.; Jones, Derek; Kerckhof, Frederiek\u2010Maarten; Kukat, Christian; Lanham, David; Leavesley, Silas; Lee, Michael; Lin\u2010Gibson, Sheng; Litwin, Virginia; Liu, Yanli; Molloy, Jenny; Moore, Jonni S.; M\u00fcller, Susann; Nedbal, Jakub; Niesner, Raluca; Nitta, Nao; Ohlsson\u2010Wilhelm, Betsy; Paul, Nicole E.; Perfetto, Stephen; Portat, Ziv; Props, Ruben; Radtke, Stefan; Rayanki, Radhika; Rieger, Aja; Rogers, Samson; Rubbens, Peter; Salomon, Robert; Schiemann, Matthias; Sharpe, John; Sonder, Soren Ulrik; Stewart, Jennifer J.; Sun, Yongliang; Ulrich, Henning; Van Isterdael, Gert; Vitaliti, Alessandra; Vreden, Caryn; Weber, Michael; Zimmermann, Jakob; Vacca, Giacomo; Wallace, Paul; T\u00e1rnok, Attila<\/b> (2019). Cyt\u2010Geist: current and future challenges in cytometry: reports of the CYTO 2018 conference workshops. <i>Cytometry A 95(6)<\/i>: 598-644. <a href=\"https:\/\/dx.doi.org\/10.1002\/cyto.a.23777\" target=\"_blank\">https:\/\/dx.doi.org\/10.1002\/cyto.a.23777<\/a>","AutID":403583,"MonDate":null,"AnaDate":2019,"PeerRev":1,"outputType":"1_A1","OpenAcc":0},{"BRefID":321900,"RR":"<b>Heyse, J.; Buysschaert, B.; Props, R.; Rubbens, P.; Skirtach, A.G.; Waegeman, W.; Boon, N.<\/b> (2019). Coculturing bacteria leads to reduced phenotypic heterogeneities. <i>Appl. Environ. Microbiol. 85(8)<\/i>: e02814-18. <a href=\"https:\/\/dx.doi.org\/10.1128\/aem.02814-18\" target=\"_blank\">https:\/\/dx.doi.org\/10.1128\/aem.02814-18<\/a>","AutID":499295,"MonDate":null,"AnaDate":2019,"PeerRev":1,"outputType":"1_A1","OpenAcc":1},{"BRefID":321915,"RR":"<b>Nguyen, B.; Rubbens, P.; Kerckhof, F.-M.; Boon, N.; De Baets, B.; Waegeman, W.<\/b> (2019). Learning single\u2010cell distances from cytometry data. <i>Cytometry A 95(7)<\/i>: 782-791. <a href=\"https:\/\/dx.doi.org\/10.1002\/cyto.a.23792\" target=\"_blank\">https:\/\/dx.doi.org\/10.1002\/cyto.a.23792<\/a>","AutID":499295,"MonDate":null,"AnaDate":2019,"PeerRev":1,"outputType":"1_A1","OpenAcc":1},{"BRefID":321916,"RR":"<b>Rubbens, P.; Schmidt, M.L.; Props, R.; Biddanda, B.A.; Boon, N.; Waegeman, W.; Denef, V.J.<\/b> (2019). Randomized Lasso links microbial taxa with aquatic functional groups inferred from flow cytometry. <i>mSystems 4(5)<\/i>: e00093-19. <a href=\"https:\/\/dx.doi.org\/10.1128\/msystems.00093-19\" target=\"_blank\">https:\/\/dx.doi.org\/10.1128\/msystems.00093-19<\/a>","AutID":499295,"MonDate":null,"AnaDate":2019,"PeerRev":1,"outputType":"1_A1","OpenAcc":1},{"BRefID":321914,"RR":"<b>Garc\u00eda-Timermans, C.; Rubbens, P.; Kerckhof, F.-M.; Buysschaert, B.; Khalenkow, D.; Waegeman, W.; Skirtach, A.G.; Boon, N.<\/b> (2018). Label-free Raman characterization of bacteria calls for standardized procedures. <i>J. microbiol. methods 151<\/i>: 69-75. <a href=\"https:\/\/dx.doi.org\/10.1016\/j.mimet.2018.05.027\" target=\"_blank\">https:\/\/dx.doi.org\/10.1016\/j.mimet.2018.05.027<\/a>","AutID":499295,"MonDate":null,"AnaDate":2018,"PeerRev":1,"outputType":"1_A1","OpenAcc":0},{"BRefID":321911,"RR":"<b>Props, R.; Rubbens, P.; Besmer, M.; Buysschaert, B.; Sigrist, J.; Weilenmann, H.; Waegeman, W.; Boon, N.; Hammes, F.<\/b> (2018). Detection of microbial disturbances in a drinking water microbial community through continuous acquisition and advanced analysis of flow cytometry data. <i>Wat. Res. 145<\/i>: 73-82. <a href=\"https:\/\/dx.doi.org\/10.1016\/j.watres.2018.08.013\" target=\"_blank\">https:\/\/dx.doi.org\/10.1016\/j.watres.2018.08.013<\/a>","AutID":499295,"MonDate":null,"AnaDate":2018,"PeerRev":1,"outputType":"1_A1","OpenAcc":0},{"BRefID":288222,"RR":"<b>Props, R.; Kerckhof, F.-M.; Rubbens, P.; De Vrieze, J.; Hernandez Sanabria, E.; Waegeman, W.; Monsieurs, P.; Hammes, F.; Boon, N.<\/b> (2017). Absolute quantification of microbial taxon abundances. <i>ISME J. 11(2)<\/i>: 584-587. <a href=\"https:\/\/dx.doi.org\/10.1038\/ismej.2016.117\" target=\"_blank\">https:\/\/dx.doi.org\/10.1038\/ismej.2016.117<\/a>","AutID":266533,"MonDate":null,"AnaDate":2017,"PeerRev":1,"outputType":"1_A1","OpenAcc":1},{"BRefID":321913,"RR":"<b>Rubbens, P.; Props, R.; Boon, N.; Waegeman, W.<\/b> (2017). Flow cytometric single-cell identification of populations in synthetic bacterial communities. <i>PLoS One 12(1)<\/i>: e0169754. <a href=\"https:\/\/dx.doi.org\/10.1371\/journal.pone.0169754\" target=\"_blank\">https:\/\/dx.doi.org\/10.1371\/journal.pone.0169754<\/a>","AutID":266533,"MonDate":null,"AnaDate":2017,"PeerRev":1,"outputType":"1_A1","OpenAcc":1},{"BRefID":321917,"RR":"<b>Rubbens, P.; Props, R.; Garcia-Timermans, C.; Boon, N.; Waegeman, W.<\/b> (2017). Stripping flow cytometry: how many detectors do we need for bacterial identification? <i>Cytometry A 91(12)<\/i>: 1184-1191. <a href=\"https:\/\/dx.doi.org\/10.1002\/cyto.a.23284\" target=\"_blank\">https:\/\/dx.doi.org\/10.1002\/cyto.a.23284<\/a>","AutID":266533,"MonDate":null,"AnaDate":2017,"PeerRev":1,"outputType":"1_A1","OpenAcc":1}],"Book":[{"BRefID":323924,"RR":"<b>Devriese, L.I.; Pirlet, H.; Nauwynck, H.; Janssen, C.; Boon, N.; Arends, J.B.A.; Maelfait, H.; Rubbens, P.; Vandegehuchte, M.; Verleye, T.; Lescrauwaet, A.-K.; Mees, J.<\/b> (2020). Fact Check. Wetenschappelijke kennis over het coronavirus SARS-CoV-2 in de context van de Vlaamse stranden. <i>VLIZ Beleidsinformerende Nota's<\/i>, 2020_003. Vlaams Instituut voor de Zee (VLIZ): Oostende. ISBN 9789492043948. 25 pp.","AutID":414631,"MonDate":2020,"AnaDate":null,"PeerRev":0,"outputType":"3_Book","OpenAcc":1}],"Thesis":[{"BRefID":321909,"RR":"<b>Rubbens, P.<\/b> (2019). Machine learning approaches for microbial flow cytometry at the single-cell and community level. PhD Thesis. Ghent University. Faculty of Bioscience Engineering: Ghent. ISBN 9789463572408. xxiv, 240 pp.","AutID":403570,"MonDate":2019,"AnaDate":null,"PeerRev":0,"outputType":"5_Thesis","OpenAcc":0},{"BRefID":321904,"RR":"<b>Rubbens, P.<\/b> (2015). Theory choice in physics. Postgraduate Thesis. University of Ghent, Faculty of Arts and Philosophy: Ghent. ii, 38 pp.","AutID":403570,"MonDate":2015,"AnaDate":null,"PeerRev":0,"outputType":"5_Thesis","OpenAcc":0},{"BRefID":321903,"RR":"<b>Rubbens, P.<\/b> (2013). Competitie - Co\u00f6rdinatie en de dynamiek van wetenschappelijke revoluties. MA Thesis. Universiteit Gent. Faculteit Wetenschappen: Gent. xii, 149 pp.","AutID":403570,"MonDate":2013,"AnaDate":null,"PeerRev":0,"outputType":"5_Thesis","OpenAcc":0}],"Abstr":[{"BRefID":321919,"RR":"<b>Garc\u00eda-Timermans, C.; Rubbens, P.; Kerckhof, F.M.; Waegeman, W.; Boon, N.<\/b> (2019). Fingerprinting microbial communities through flow cytometry and Raman spectroscopy, <b><i>in<\/i><\/b>: <i>BAGECO 15. 15th Symposium on Bacterial Genetics and Ecology: \"Ecosystem drivers in a changing planet\", 26\u201330 May 2019, Lisbon\/Portugal.<\/i> pp. 155","AutID":403631,"MonDate":null,"AnaDate":2019,"PeerRev":0,"outputType":"6_Abstr","OpenAcc":1}]},"urls":[{"URL":"https:\/\/orcid.org\/0000-0001-5595-4758","externalID":"0000-0001-5595-4758","URLTypeCode":"ORCID","URLType":"ORCID"}],"spcols":null,"thesterms":[{"ThesaurusTerm":"Classical physics not elsewhere classified","Code":"01030399","ThestID":178978,"ThesTypID":23,"ThesType":"Flemish Research Disciplines"}],"taxterms":null,"pub":1,"newses":{"SesID":95808,"LoginName":"VLIZ2000\\ruthv","LoginID":79,"DD":"2019-10-14"},"updses":{"SesID":95808,"LoginName":"VLIZ2000\\ruthv","LoginID":79,"DD":"2019-10-14"},"urlmaps":[],"resmessage":"no id specified","complete":1}
