Mapping Bacterial Cell States Across Environments and Evolution

Synthesizes bacterial gene expression data to create the first atlas of cell states including growth, starvation, biofilm formation, and dormancy across diverse environments. Develops machine learning classifiers predicting bacterial phenotypes from metagenomic data.

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Author Jeffrey Barrick
Last Updated September 10, 2026, 18:10 (UTC)
Published August 5, 2026, 18:10 (UTC)
Citation Jeffrey Barrick 2025. Mapping Bacterial Cell States Across Environments and Evolution. CyVerse Data Commons.
Description Synthesizes bacterial gene expression data to create the first atlas of cell states including growth, starvation, biofilm formation, and dormancy across diverse environments. Develops machine learning classifiers predicting bacterial phenotypes from metagenomic data.
PublicationYear 2025
Publisher CyVerse Data Commons
Rights This material is based upon work supported by the U.S. National Science Foundation under Award No. #2335029. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the U.S. National Science Foundation.
Subject bacterial genomics, cell states, gene expression, machine learning, environmental adaptation, metagenomics
de_created_date 2025-03-31T13:55:12Z
de_modified_date 2026-08-03T20:20:54Z