Author

Justin A. Sanders

University of Washington

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Biochemistry· 1 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Assay:proteomics· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Organism:mouse· 1 Research Focus:variant calling· 1

Frequent Co-Authors

William Stafford NobleiD· 2 shared Alec Morimoto· 1 shared Alex ZelteriD· 1 shared Antoine M. SnijdersiD· 1 shared Batool Mutawe· 1 shared Benjamin A. ShaveriD· 1 shared Christine C WuiD· 1 shared Daniel ChelskyiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBiochemistry

William Stafford NobleORCID

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2 papers

Recent·Most cited

BiochemistrybioRxivPreprintMay 22, 2026

A quantitative proteomics dataset for assessment and prediction of low dose X-ray radiation exposure in mice.

Alex Zelter, Michael E. Riffle, Gennifer E. Merrihew…·Michael J. MacCoss

The paper presents two large-scale proteomics datasets from mice exposed to varying X-ray doses and time points, enabling biomarker discovery and machine learning applications for radiation exposure assessment.

1 citation

mouseproteomics

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BioinformaticsbioRxivPreprintSep 12, 2025

A procedure for controlling the false discovery rate of de novopeptide sequencing

Justin A. Sanders, William Stafford Noble, Uri Keich

The paper introduces an FDR control procedure for de novo peptide sequencing and demonstrates its validity and utility.

DOI 10.1101/2025.09.12.675837

proteomicsstatistical model

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