Author

Sarah C. Jenson

Pacific Northwest National LaboratoryORCID 0000-0002-0807-5651Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Assay:proteomics· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Assay:metagenomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Eric D. MerkleyiD· 2 shared Aleksey Y. OgurtsoviD· 1 shared Anthony S. BarenteiD· 1 shared Carrie NicoraiD· 1 shared Dustin L. Crockett· 1 shared Ernesto Satoshi NakayasuiD· 1 shared Fanny ChuiD· 1 shared Gelio AlvesiD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersBioinformatics

Eric D. MerkleyORCID

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2 papers

Recent·Most cited

MARLOWE: Taxonomic Characterization of Unknown Samples for Forensics Using De Novo Peptide Identification

Sarah C. Jenson, Fanny Chu, Gelio Alves, Aleksey Y. Ogurtsov, Anthony S. Barente, Dustin L. Crockett, Natalie C. Lamar, Eric D. Merkley, Yi‐Kuo Yu, Kristin H. Jarman

MARLOWE is a computational tool for taxonomic characterization of unknown forensic samples using de novo peptide identification, achieving high specificity in species-level identification.

Scientific Reports · Aug 20, 2026Peer-reviewedBioinformatics

Uncovering hidden members and functions of the soil microbiome using de novo metaproteomics

Joon‐Yong Lee, Hugh D. Mitchell, Meagan Burnet, Ruonan Wu, Sarah C. Jenson, Eric D. Merkley, Ernesto Satoshi Nakayasu, Carrie Nicora, Janet K Jansson, Kristin Burnum-Johnson, Samuel Payne

This paper introduces a de novo metaproteomics pipeline using a deep learning model to identify soil microbiome composition and functions without relying on metagenomic data.

Journal of Proteome Research · Jul 6, 2022Peer-reviewedBioinformatics