Author

Eric V. Anslyn

The University of Texas at AustinORCID 0000-0002-5137-8797Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Molecular Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Assay:proteomics· 1

Frequent Co-Authors

Daniel WinkleriD· 2 shared Edward M. MarcotteiD· 2 shared Alexander Dunmyre· 1 shared Andrew D. EllingtoniD· 1 shared Angela M. BardoiD· 1 shared Ayesha J. S. MahmoodiD· 1 shared Casey J. Howdieshell· 1 shared Christopher Martin· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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2 shared papersBioinformatics

Daniel WinklerORCID

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2 papers

Recent·Most cited

Learning from human and chemical languages to predict biological function

Clayton W. Kosonocky, Nikol Kadeřábková, Kangsan Kim, Ayesha J. S. Mahmood, Alexander Dunmyre, Phillip R. Woolley, Kristi Xing, Daniel Winkler, Tomer Babu, Filip Kadeřábek, Jonathan L. Sessler, Eric V. Anslyn, Edward M. Marcotte, Yan Zhang, Andrew D. Ellington, Despoina A. I. Mavridou

This paper introduces a deep learning model that predicts biological function from chemical structure using scientific literature, identifying effective inhibitors of beta-lactamases.

bioRxiv · Aug 17, 2026 · PreprintBioinformatics

Robust and scalable single-molecule protein sequencing with fluorosequencing

James Mapes, Julia Stover, Heather D. Stout, Tucker M. Folsom, Emily Babcock, Sandra Loudwig, Christopher Martin, Mariah J. Austin, Fan Tu, Casey J. Howdieshell, Zachary Booth Simpson, Thomas Blom, Daniel C. Weaver, Daniel Winkler, Kent Vander Velden, , Jagannath Swaminathan

This paper improves fluorosequencing by optimizing fluorophores, reducing dye interactions, and creating an end-to-end workflow, demonstrating its potential for high-sensitivity clinical proteomics.

bioRxiv · Sep 15, 2023 · PreprintMolecular Biology