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FEBS Letters
|
March 4, 2014
The dynamic microbiome
Georg K Gerber
Cell Host & Microbe
|
August 15, 2024
AI in microbiome research: Where have we been, where are we going?
Georg K Gerber
Microbiome
|
December 9, 2025
MMETHANE: interpretable AI for predicting host status from microbial composition and metabolomics data
Jennifer J Dawkins, Georg K Gerber
Biorxiv : the Preprint Server for Biology
|
December 23, 2024
MMETHANE: interpretable AI for predicting host status from microbial composition and metabolomics data
Jennifer J Dawkins, Georg K Gerber
Genome Biology
|
September 4, 2019
MITRE: inferring features from microbiota time-series data linked to host status
Elijah Bogart, Richard Creswell, Georg K Gerber
Plos Computational Biology
|
August 10, 2012
Inferring dynamic signatures of microbes in complex host ecosystems
Georg K Gerber, Andrew B Onderdonk, Lynn Bry
Msystems
|
September 7, 2022
MDITRE: Scalable and Interpretable Machine Learning for Predicting Host Status from Temporal Microbiome Dynamics
Venkata Suhas Maringanti, Vanni Bucci, Georg K Gerber
Plos Computational Biology
|
August 19, 2007
Automated discovery of functional generality of human gene expression programs
Georg K Gerber, Robin D Dowell, Tommi S Jaakkola, et al.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|
August 26, 2003
Continuous representations of time-series gene expression data
Ziv Bar-Joseph, Georg K Gerber, David K Gifford, et al.
Digestive Diseases and Sciences
|
November 1, 2019
Clinical Predictors of Recurrence After Primary Clostridioides difficile Infection: A Prospective Cohort Study
Jessica R Allegretti, Jenna Marcus, Margaret Storm, et al.
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Search research articles
Search
Showing results (1-10 of 43) with videos related to
Sort By:
Page
of 5
FEBS Letters
|
March 4, 2014
The dynamic microbiome
Georg K Gerber
Cell Host & Microbe
|
August 15, 2024
AI in microbiome research: Where have we been, where are we going?
Georg K Gerber
Microbiome
|
December 9, 2025
MMETHANE: interpretable AI for predicting host status from microbial composition and metabolomics data
Jennifer J Dawkins, Georg K Gerber
Biorxiv : the Preprint Server for Biology
|
December 23, 2024
MMETHANE: interpretable AI for predicting host status from microbial composition and metabolomics data
Jennifer J Dawkins, Georg K Gerber
Genome Biology
|
September 4, 2019
MITRE: inferring features from microbiota time-series data linked to host status
Elijah Bogart, Richard Creswell, Georg K Gerber
Plos Computational Biology
|
August 10, 2012
Inferring dynamic signatures of microbes in complex host ecosystems
Georg K Gerber, Andrew B Onderdonk, Lynn Bry
Msystems
|
September 7, 2022
MDITRE: Scalable and Interpretable Machine Learning for Predicting Host Status from Temporal Microbiome Dynamics
Venkata Suhas Maringanti, Vanni Bucci, Georg K Gerber
Plos Computational Biology
|
August 19, 2007
Automated discovery of functional generality of human gene expression programs
Georg K Gerber, Robin D Dowell, Tommi S Jaakkola, et al.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|
August 26, 2003
Continuous representations of time-series gene expression data
Ziv Bar-Joseph, Georg K Gerber, David K Gifford, et al.
Digestive Diseases and Sciences
|
November 1, 2019
Clinical Predictors of Recurrence After Primary Clostridioides difficile Infection: A Prospective Cohort Study
Jessica R Allegretti, Jenna Marcus, Margaret Storm, et al.
Page
of 5