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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
Cynthia L. Darnell
Biology Department, Duke University, Durham, 27708, USA
Francesca M.L. Bushell
School of Biosciences, University of Birmingham, Birmingham, United Kingdom
Peter A. Lund
School of Biosciences, University of Birmingham, Birmingham, United Kingdom
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
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
Posted October 04, 2019.
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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