Author

Ethan Bustad

Seattle Children's Research InstituteORCID 0000-0002-0230-2913Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Immunology· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Organism:mouse· 1 Assay:scRNA-seq· 1 Approach:statistical model· 1

Frequent Co-Authors

Shuyi MaiD· 2 shared Alan H. DiercksiD· 1 shared Alexis KaushanskyiD· 1 shared Alissa C. RothchildiD· 1 shared Benjamin Henry GerniD· 1 shared Braden T GriebeliD· 1 shared Courtney Ray PlumleeiD· 1 shared David R. ShermaniD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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2 shared papersImmunology

Shuyi MaORCID

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2 papers

Recent·Most cited

Modulation of Ferroptosis During Early Mycobacterium tuberculosis Infection Contributes to Beijing Lineage Strain SA161 Virulence

Josh Ivie, Sylvia M. Stull, Ethan Bustad, Courtney Ray Plumlee, Sara Beth Cohen, Fergal J. Duffy, Alan H. Diercks, John D. Aitchison, Kevin B. Urdahl, Alexis Kaushansky, Alissa C. Rothchild, Benjamin Henry Gern, Shuyi Ma

This study shows that ferroptosis, a form of cell death, is enhanced by a virulent Mtb strain, SA161, and inhibiting it reduces bacterial spread in mice.

bioRxiv · Jun 4, 2026 · PreprintImmunology

Predicting bacterial fitness in Mycobacterium tuberculosis with transcriptional regulatory network-informed interpretable machine learning

Ethan Bustad, Edson Petry, Oliver Gu, Braden T Griebel, Tige R. Rustad, David R. Sherman, Jason H. Yang, Shuyi Ma

The paper predicts Mtb fitness using a transcription factor activity-based machine learning model trained on RNA-seq data and regulatory network analysis.

Frontiers in Tuberculosis · Apr 2, 2025Peer-reviewedSystems Biology