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Justin D Silverman

Showing results (1-10 of 37) with videos related to

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Biorxiv : the Preprint Server for Biology|August 6, 2025
PCR Bias Impacts Microbiome Ecological AnalysesDharmik Rathod, Justin D Silverman
BMC Bioinformatics|July 2, 2025
Replacing normalizations with interval assumptions enhances differential expression and differential abundance analysesKyle C McGovern, Justin D Silverman
Microbiome|March 26, 2026
Scale reliant mixed effects models enhance microbiome data analysisKyle C McGovern, Justin D Silverman
Plos Computational Biology|January 27, 2026
PCR bias impacts microbiome ecological analysesDharmik R Rathod, Justin D Silverman
Proceedings of Machine Learning Research|January 8, 2026
Scalable Inference for Bayesian Multinomial Logistic-Normal Dynamic Linear ModelsManan Saxena, Tinghua Chen, Justin D Silverman
Science Translational Medicine|June 24, 2020
Using influenza surveillance networks to estimate state-specific prevalence of SARS-CoV-2 in the United StatesJustin D Silverman, Nathaniel Hupert, Alex D Washburne
Biorxiv : the Preprint Server for Biology|April 15, 2024
Beyond Normalization: Incorporating Scale Uncertainty in Microbiome and Gene Expression AnalysisMichelle Pistner Nixon, Gregory B Gloor, Justin D Silverman
Plos Computational Biology|November 20, 2023
Addressing erroneous scale assumptions in microbe and gene set enrichment analysisKyle C McGovern, Michelle Pistner Nixon, Justin D Silverman
NAR Genomics and Bioinformatics|August 21, 2025
Explicit Scale Simulation for analysis of RNA-sequencing count data with ALDEx2Gregory B Gloor, Michelle Pistner Nixon, Justin D Silverman
Biorxiv : the Preprint Server for Biology|September 26, 2025
Uncertainty Modeling Outperforms Machine Learning for Microbiome Data AnalysisMaxwell A Konnaris, Manan Saxena, Nicole Lazar, et al.
Pageof 4

Showing results (1-10 of 37) with videos related to

Sort By:
Pageof 4
Biorxiv : the Preprint Server for Biology|August 6, 2025
PCR Bias Impacts Microbiome Ecological AnalysesDharmik Rathod, Justin D Silverman
BMC Bioinformatics|July 2, 2025
Replacing normalizations with interval assumptions enhances differential expression and differential abundance analysesKyle C McGovern, Justin D Silverman
Microbiome|March 26, 2026
Scale reliant mixed effects models enhance microbiome data analysisKyle C McGovern, Justin D Silverman
Plos Computational Biology|January 27, 2026
PCR bias impacts microbiome ecological analysesDharmik R Rathod, Justin D Silverman
Proceedings of Machine Learning Research|January 8, 2026
Scalable Inference for Bayesian Multinomial Logistic-Normal Dynamic Linear ModelsManan Saxena, Tinghua Chen, Justin D Silverman
Science Translational Medicine|June 24, 2020
Using influenza surveillance networks to estimate state-specific prevalence of SARS-CoV-2 in the United StatesJustin D Silverman, Nathaniel Hupert, Alex D Washburne
Biorxiv : the Preprint Server for Biology|April 15, 2024
Beyond Normalization: Incorporating Scale Uncertainty in Microbiome and Gene Expression AnalysisMichelle Pistner Nixon, Gregory B Gloor, Justin D Silverman
Plos Computational Biology|November 20, 2023
Addressing erroneous scale assumptions in microbe and gene set enrichment analysisKyle C McGovern, Michelle Pistner Nixon, Justin D Silverman
NAR Genomics and Bioinformatics|August 21, 2025
Explicit Scale Simulation for analysis of RNA-sequencing count data with ALDEx2Gregory B Gloor, Michelle Pistner Nixon, Justin D Silverman
Biorxiv : the Preprint Server for Biology|September 26, 2025
Uncertainty Modeling Outperforms Machine Learning for Microbiome Data AnalysisMaxwell A Konnaris, Manan Saxena, Nicole Lazar, et al.
Pageof 4