Author

Paul Carini

University of ArizonaORCID 0000-0002-9653-7309Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Paul Carini2 papers

Biology Disciplines

Click to filter author papers

Microbiology· 2

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:bacteria (other)· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Assay:metabolomics· 1 Organism:multiple species· 1

Frequent Co-Authors

Adriana C. Gomez-BuckleyiD· 1 shared Alexander Crits‐ChristophiD· 1 shared Benjamin P. BoweniD· 1 shared Christina R. GuerreroiD· 1 shared Henry H. LeeiD· 1 shared Isabella A. VineyiD· 1 shared Katherine LouieiD· 1 shared Laura MeredithiD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperMicrobiology

Adriana C. Gomez-BuckleyORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Transcriptional and metabolic stasis define desiccation-induced dormancy in the soil bacterium Arthrobacter sp. AZCC_0090 until water vapor initiates resuscitation.

Paul Carini, Adriana C. Gomez-Buckley, Christina R. Guerrero, Melanie R Kridler, Isabella A. Viney, Roya AminiTabrizi, M. M. Tfaily, Peter Moma, Laura Meredith, Katherine Louie, Benjamin P. Bowen, Trent R. Northen, Oona Snoeyenbos-West, Ryan P. Bartelme

This study shows that desiccation-induced dormancy in Arthrobacter sp. AZCC_0090 preserves mRNA and metabolite profiles, with changes only occurring during drying and rehydration transitions.

mSystems · Feb 6, 2026Peer-reviewedMicrobiology

Predicting microbial growth conditions from amino acid composition

Tyler P. Barnum, Alexander Crits‐Christoph, Michael N. Molla, Paul Carini, Henry H. Lee, Nili Ostrov

This paper develops genome-based models to predict microbial growth conditions using amino acid composition, showing high accuracy for oxygen tolerance, temperature, salinity, and pH.

bioRxiv · Mar 22, 2024 · PreprintMicrobiology