Author

Jaylen E. Taylor

University of Maryland, BaltimoreORCID 0000-0001-9455-3578Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Biophysics· 2

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Approach:deep learning· 2 Research Focus:protein folding & dynamics· 2 Assay:proteomics· 2 Research Focus:benchmarking· 1 Approach:machine learning (classical)· 1 Research Focus:sequence-to-function modeling· 1 Approach:statistical model· 1

Frequent Co-Authors

Bryan A. KrantziD· 2 shared Parichit SharmaiD· 2 shared

Activity by Year

2026-2026 · peak 2/yr

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2 top collaborators · 1 mutual co-author link

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2 shared papersBiophysics

Bryan A. KrantzORCID

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2 papers

Recent·Most cited

BiophysicsbioRxivPreprintAug 20, 2026

Single-Molecule Proteomics via a Dynamic Translocase and Physics-Informed Machine Learning

Jaylen E. Taylor, Parichit Sharma, Bryan A. Krantz

This paper introduces a dynamic translocase and physics-informed machine learning to resolve isobaric amino acids at the single-molecule level with high accuracy.

DOI 10.64898/2026.08.17.745284

proteomicsdeep learning

𝕏 PostBluesky

BiophysicsbioRxivPreprintJul 23, 2026

Beyond the Static Caliper: Dynamical Translocases and the Mathematical Imperative for Single-Molecule Proteomics

Jaylen E. Taylor, Parichit Sharma, Bryan A. Krantz

This paper proposes dynamical translocases and Physics-Informed Machine Learning to overcome biophysical limitations in single-molecule proteomics, achieving >90% accurate amino acid classification.

DOI 10.64898/2026.07.20.739629

proteomicsdeep learning

𝕏 PostBluesky