Author

Trent B. Hinkle

GenentechORCID 0000-0001-9090-2750Unclaimed 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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Organism:human· 2 Assay:proteomics· 2 Approach:statistical model· 2 Research Focus:differential expression· 1 Assay:metagenomics· 1 Organism:mouse· 1 Organism:multiple species· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Corey E. BakalarskiiD· 1 shared Devon KohleriD· 1 shared Erik VerschuereniD· 1 shared Lilian Phu· 1 shared Meena ChoiiD· 1 shared Olga Vitek AiD· 1 shared Ting C. HuangiD· 1 shared Tsung‐Heng TsaiiD· 1 shared

Activity by Year

2022-2024 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 21 mutual co-author links

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1 shared paperBioinformatics

Corey E. BakalarskiORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintOct 17, 2024

Joint Protein Inference Analysis with PyProteinInference Elucidates Biological Understanding of Tandem Mass Spectrometry Data

Trent B. Hinkle, Corey E. Bakalarski

PyProteinInference enables joint protein inference analysis of MS/MS data to compute protein-level FDR and support biological interpretation.

DOI 10.1101/2024.10.17.618892

humanproteomics

𝕏 PostBluesky

BioinformaticsMolecular & Cellular ProteomicsPeer-reviewedDec 8, 2022

MSstatsPTM: Statistical relative quantification of post-translational modifications in bottom-up mass spectrometry-based proteomics

Devon Kohler, Tsung‐Heng Tsai, Erik Verschueren…·Olga Vitek A

The paper introduces a statistical framework for detecting differential post-translational modification abundance in proteomics data, showing improved fold change estimation and detection compared to existing methods.

53 citations

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