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A Bayesian Non-parametric Mixed-Effects Model of Microbial Phenotypes

Peter D. Tonner, Cynthia L. Darnell, Francesca M.L. Bushell, Peter A. Lund, Amy K. Schmid, Scott C. Schmidler
doi: https://doi.org/10.1101/793174
Peter D. Tonner
Program in Computational Biology and Bioinformatics, Duke University, Durham, 27708, USABiology Department, Duke University, Durham, 27708, USA
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Cynthia L. Darnell
Biology Department, Duke University, Durham, 27708, USA
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Francesca M.L. Bushell
School of Biosciences, University of Birmingham, Birmingham, United Kingdom
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Peter A. Lund
School of Biosciences, University of Birmingham, Birmingham, United Kingdom
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Amy K. Schmid
Program in Computational Biology and Bioinformatics, Duke University, Durham, 27708, USABiology Department, Duke University, Durham, 27708, USACenter for Genomics and Computational Biology, Duke University, Durham, 27708, USA
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  • For correspondence: amy.schmid@duke.edu
Scott C. Schmidler
Program in Computational Biology and Bioinformatics, Duke University, Durham, 27708, USADepartment of Statistical Science, Duke University, Durham, 27708, USADepartment of Computer Science, Duke University, Durham, 27708, USA
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  • https://github.com/ptonner/phenom

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Posted October 04, 2019.
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A Bayesian Non-parametric Mixed-Effects Model of Microbial Phenotypes
Peter D. Tonner, Cynthia L. Darnell, Francesca M.L. Bushell, Peter A. Lund, Amy K. Schmid, Scott C. Schmidler
bioRxiv 793174; doi: https://doi.org/10.1101/793174
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A Bayesian Non-parametric Mixed-Effects Model of Microbial Phenotypes
Peter D. Tonner, Cynthia L. Darnell, Francesca M.L. Bushell, Peter A. Lund, Amy K. Schmid, Scott C. Schmidler
bioRxiv 793174; doi: https://doi.org/10.1101/793174

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