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LITERATURE CITED

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    Talbot G, Topp E, Palin MF, Massé DI. Evaluation of molecular methods used for establishing the interactions and functions of microorganisms in anaerobic bioreactors. Water Res 2008; 42: 513537.
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    Morales SE, Holben WE. Linking bacterial identities and ecosystem processes: Can ‘omic’ analyses be more than the sum of their parts?. FEMS Microbiol Ecol 2011; 75: 216.
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    Günther S, Koch C, Hübschmann T, Röske I, Müller RA, Bley T, Harms H, Müller S. Correlation of community dynamics and process parameters as a tool for the prediction of the stability of wastewater treatment. Environ Sci Technol 2012; 46: 8492.
  • 4
    Günther S, Trutnau M, Kleinsteuber S, Hause G, Bley, T, Röske I, Harms H, Müller S. Dynamics of polyphosphate-accumulating bacteria in wastewater treatment plant microbial communities detected via DAPI (4′,6′-diamidino-2-phenylindole) and tetracycline labeling. Appl Environ Microbiol 2009; 75: 21112121.
  • 5
    Koch C, Günther S, Desta AF, Hübschmann T, Müller S. Cytometric fingerprinting for analysing microbial intra-community structure variation and identifying sub-community function. Nat Protocols 2013; 8: 190202.
  • 6
    Boddy L, Wilkins MF, Morris CW. Pattern recognition in flow cytometry. Cytometry 2001; 44: 195209.
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    Bashashati A, Brinkman R. A survey of flow cytometry data analysis methods. Adv Bioinformatics 2009; Article ID 584603.
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    Roederer M, Moore W, Treister A, Hardy RR, Herzenberg LA. Probability binning comparison: A metric for quantitating multivariate distribution differences. Cytometry 2001; 45: 4755.
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    Rogers WT, Holyst HA. FlowFP: A bioconductor package for fingerprinting flow cytometric data. Adv Bioinformatics 2009: 193947.
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    De Roy K, Clement L, Thas O, Wang Y, Boon N. Flow cytometry for fast microbial community fingerprinting. Water Res 2012; 46: 907919.
  • 11
    Bombach P, Hübschmann T, Fetzer I, Kleinsteuber S, Geyer R, Harms H, Müller S. Resolution of natural microbial community dynamics by community fingerprinting, flow cytometry, and trend interpretation analysis. In: Müller S,Bley T, editors. Advances in Biochemical Engineering and Biotechnology, Vol. 124. Berlin: Springer; 2011. pp 151181.
  • 12
    Müller S, Hübschmann T, Kleinsteuber S, Vogt C. High resolution single cell analytics to follow microbial community dynamics in anaerobic ecosystems. Methods 2012; 57: 338349.
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    Müller S. Modes of cytometric bacterial DNA pattern: A tool for pursuing growth. Cell Prolif 2007; 40: 621639.
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    Günther S, Hübschmann T, Rudolf M, Eschenhagen M, Röske I, Harms H, Müller S. Fixation procedures for flow cytometric analysis of environmental bacteria. J Microbiol Methods 2008; 75: 127134.
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    Schneider CA, Rasband WS, Eliceiri KW. NIH image to ImageJ: 25 years of image analysis. Nat Methods 2012; 9: 671675.
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    R Development Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2011. Available at http://www.R-project.org/.
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    Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O'Hara RB, Simpson GL, Solymos P, Stevens MHH, Wagner H. Vegan: Community ecology package. R package version 1.17-10. 2011. Available at http://CRAN.R-project.org/package=vegan.
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    Hamady M, Knight R. Microbial community profiling for human microbiome projects: Tools, techniques, and challenges. Genome Res 2009; 19: 11411152.
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    Werner JJ, Knights D, Garcia ML, Scalfone NB, Smith S, Yarasheski K, Cummings TA, Beers AR, Knight R, Angenent LT. Bacterial community structures are unique and resilient in full-scale bioenergy systems. Proc Natl Acad Sci USA 2011; 108: 41584163.
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    Sarkar D, Le Meur N, Gentleman R. Using flowViz to visualize flow cytometry data. Bioinformatics 2008; 24: 878879.
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    Lee K, Hahne F, Sarkar D, Gentleman R. iFlow: A graphical user interface for flow cytometry tools in bioconductor. Adv Bioinformatics 2009: 103839.