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Molly G Hayes

Showing results (1-10 of 4) with videos related to

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BMC Bioinformatics|October 8, 2023
Cross-study analyses of microbial abundance using generalized common factor methodsMolly G Hayes, Morgan G I Langille, Hong Gu
Bioinformatics (Oxford, England)|September 30, 2022
Integrating phylogenetic and functional data in microbiome studiesGavin M Douglas, Molly G Hayes, Morgan G I Langille, et al.
Nature Communications|January 18, 2022
Microbiome differential abundance methods produce different results across 38 datasetsJacob T Nearing, Gavin M Douglas, Molly G Hayes, et al.
Nature Communications|February 4, 2022
Author Correction: Microbiome differential abundance methods produce different results across 38 datasetsJacob T Nearing, Gavin M Douglas, Molly G Hayes, et al.
Pageof 1

Showing results (1-10 of 4) with videos related to

Sort By:
Pageof 1
BMC Bioinformatics|October 8, 2023
Cross-study analyses of microbial abundance using generalized common factor methodsMolly G Hayes, Morgan G I Langille, Hong Gu
Bioinformatics (Oxford, England)|September 30, 2022
Integrating phylogenetic and functional data in microbiome studiesGavin M Douglas, Molly G Hayes, Morgan G I Langille, et al.
Nature Communications|January 18, 2022
Microbiome differential abundance methods produce different results across 38 datasetsJacob T Nearing, Gavin M Douglas, Molly G Hayes, et al.
Nature Communications|February 4, 2022
Author Correction: Microbiome differential abundance methods produce different results across 38 datasetsJacob T Nearing, Gavin M Douglas, Molly G Hayes, et al.
Pageof 1