W. D. Wadsworth

Title An integrative Bayesian Dirichlet-multinomial regression model for the analysis of taxonomic abundances in microbiome data Permalink

M. Vannucci, M. Guindani, R. Argiento, 2017 .

The role of the gastrointestinal microbiome in infectious complications during induction chemotherapy for acute myeloid leukemia

Daniel Patrick Smith, N. Ajami, J. Petrosino, 2016, Cancer.

Characterization of oral and gut microbiome temporal variability in hospitalized cancer patients

Daniel Patrick Smith, N. Ajami, J. Petrosino, 2017, Genome Medicine.

Characterization of the human gut microbiome during travelers' diarrhea

N. Ajami, J. Petrosino, Bonnie P. Youmans, 2015, Gut microbes.

An integrative Bayesian Dirichlet-multinomial regression model for the analysis of taxonomic abundances in microbiome data

Marina Vannucci, Raffaele Argiento, Michele Guindani, 2017, BMC Bioinformatics.

Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

Laura Winther Balling, Sarah M. G. Otner, Patrick K. O'Neill, 2021, Organizational Behavior and Human Decision Processes.

Two‐group Poisson‐Dirichlet mixtures for multiple testing

Marina Vannucci, Fabrizio Leisen, Michele Guindani, 2020, Biometrics.

Reduced transpiration response to precipitation pulses precedes mortality in a piñon-juniper woodland subject to prolonged drought.

N. McDowell, W. Pockman, J. Plaut, 2013, The New phytologist.

Empirical Evaluation of Federated Learning with Local Privacy for Real-World Application

P. Li, W. D. Wadsworth, Jilong Liao, 2020, 2020 IEEE International Conference on Big Data (Big Data).

An integrative Bayesian Dirichlet-multinomial regression model for the analysis of taxonomic abundances in microbiome data

M. Vannucci, M. Guindani, R. Argiento, 2017, BMC Bioinformatics.