MDITRE: Scalable and Interpretable Machine Learning for Predicting Host Status from Temporal Microbi...
MDITRE: Scalable and Interpretable Machine Learning for Predicting Host Status from Temporal Microbiome Dynamics
About this item
Full title
Author / Creator
Publisher
United States: American Society for Microbiology
Journal title
Language
English
Formats
Publication information
Publisher
United States: American Society for Microbiology
Subjects
More information
Scope and Contents
Contents
The human microbiome, or collection of microbes living on and within us, changes over time. Linking these changes to the status of the human host is crucial to understanding how the microbiome influences a variety of human diseases.
Longitudinal microbiome data sets are being generated with increasing regularity, and there is broad recognition t...
Alternative Titles
Full title
MDITRE: Scalable and Interpretable Machine Learning for Predicting Host Status from Temporal Microbiome Dynamics
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_352d851cf8074abbaedfe168744847f5
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_352d851cf8074abbaedfe168744847f5
Other Identifiers
ISSN
2379-5077
E-ISSN
2379-5077
DOI
10.1128/msystems.00132-22
