Author

Danielle S. LeSassier

ORCID 0000-0002-7932-5064Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genomics· 2 Bioinformatics· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Approach:statistical model· 3 Research Focus:benchmarking· 2 Assay:metagenomics· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:database / resource· 1 Approach:deep learning· 1

Frequent Co-Authors

Krista L. TernusiD· 3 shared Anthony D. KappelliD· 2 shared F. Curtis HewittiD· 2 shared Gene D. GodboldiD· 2 shared Advait BalajiiD· 1 shared Amanda N. ScholesiD· 1 shared Bingbing HuiD· 1 shared Brandon Niese· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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3 shared papersMicrobiology

Krista L. TernusORCID

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Predicting neutron radiation exposure characteristics from an in vitro human skin model using RNA-seq

Myles W. Gardner, Danielle S. LeSassier, Joshua C. Gil, Jesse C. Werth, Madeleine Pont, Guy Y. Garty, Elizabeth A Scheuermann, Helen C. Turner, Patrick J. Cocola, Charles Richmond Grice, Viviana M. June, Catie A. Vaccaro, Brooke E. Tashner, F. Curtis Hewitt

This study uses RNA-seq to identify molecular signatures in human skin models that predict neutron radiation exposure and temporal response.

bioRxiv · Jan 30, 2026 · PreprintGenomics

Predicting characterization of microbiome taxonomy from imaging using machine learning approaches

Brandon Niese, Philip Sweet, Bryan Dinh, Amanda N. Scholes, Danielle S. LeSassier, Krista L. Ternus, Lydia M. Contreras, Vernita Diane Gordon

This paper uses machine learning on microscopy images to predict microbial community taxonomic diversity and dominant bacterial classes, achieving high accuracy and low error.

bioRxiv · Feb 3, 2025 · PreprintMicrobiology

SeqScreen-Nano: a computational platform for rapid, in-field characterization of previously unseen pathogens.

Advait Balaji, Yunxi Liu, Michael Nute, Bingbing Hu, Anthony D. Kappell, Danielle S. LeSassier, Gene D. Godbold, Krista L. Ternus, Todd J. Treangen

SeqScreen-Nano rapidly characterizes novel pathogens using ONT sequencing in resource-limited settings by identifying ORFs and classifying them functionally and taxonomically.

bioRxiv · Feb 10, 2023 · PreprintBioinformatics

Detection of ESKAPE pathogens and Clostridioides difficile in Simulated Skin Transmission Events with Metagenomic and Metatranscriptomic Sequencing

Krista L. Ternus, Nicolette C. Keplinger, Anthony D. Kappell, Gene D. Godbold, Veena Palsikar, Carlos A. Acevedo, Katharina L. Weber, Danielle S. LeSassier, Kathleen Q. Schulte, Nicole Westfall, F. Curtis Hewitt

This study evaluates NGS-based methods for detecting healthcare-acquired pathogens in simulated skin transmission events using metagenomic and metatranscriptomic sequencing.

bioRxiv · Mar 4, 2021 · PreprintGenomics