Author

Anton V. Persikov

Flatiron InstituteORCID 0000-0001-8106-5794Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:biophysical modeling· 1 Assay:ChIP-seq· 1 Approach:deep learning· 1 Organism:Drosophila· 1 Organism:human· 1 Research Focus:protein folding & dynamics· 1 Assay:proteomics· 1 Research Focus:sequence-to-function modeling· 1

Frequent Co-Authors

Amina KurbidaevaiD· 1 shared Brendan Wang· 1 shared Gabriel A. Dolsten· 1 shared James B. JaynesiD· 1 shared Michael S. LevineiD· 1 shared Miki FujiokaiD· 1 shared Mona SinghiD· 1 shared Paul D. SchedliD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperGenomics

Amina KurbidaevaORCID

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2 papers

Recent·Most cited

BiophysicsBiophysical JournalPeer-reviewedJun 24, 2026

Local sequence context determines the effect of glycine substitutions in collagen triple helices

Anton V. Persikov

The paper shows that glycine substitutions in collagen triple helices have varying effects based on local sequence context, with GP sites being especially restrictive.

DOI 10.1016/j.bpj.2026.06.028

humanproteomics

𝕏 PostBluesky

GenomicsbioRxivPreprintJun 19, 2026

Sequence-to-function modeling uncovers the context-specific grammar of Drosophila chromatin insulation

Brendan Wang, Gabriel A. Dolsten, Wenfan Ke…·Yuri Pritykin

The paper introduces Domino, a deep learning framework that models sequence-to-function relationships to uncover the context-specific grammar of Drosophila chromatin insulation.

2 citations

DrosophilaChIP-seq

𝕏 PostBluesky