Author

Jeffrey L. Thorne

North Carolina State UniversityORCID 0000-0003-3779-5743Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Evolutionary Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:phylogenetics / evolution· 1 Assay:protein sequence· 1 Approach:statistical model· 1

Frequent Co-Authors

Haim AshkenazyiD· 1 shared Itay MayroseiD· 1 shared Ksenia PolonskyiD· 1 shared Nimrod SerokiD· 1 shared Tae‐Kun SeoiD· 1 shared Tal PupkoiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

6 top collaborators · 10 mutual co-author links

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1 shared paperBioinformatics

Haim AshkenazyORCID

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2 papers

Recent·Most cited

BioinformaticsMolecular Biology and EvolutionPeer-reviewedJul 20, 2026

A deep-learning-based score to evaluate multiple sequence alignments

Nimrod Serok, Ksenia Polonsky, Haim Ashkenazy…·Tal Pupko

The paper develops deep-learning-based scores to assess MSA quality, showing they outperform the SP score in identifying accurate alignments and improving phylogenetic reconstruction.

1 citation

protein sequencedeep learning

𝕏 PostBluesky

Evolutionary BiologybioRxivPreprintOct 15, 2025

Likelihood-based evaluation of character recoding schemes for phylogenetic analysis

Tae‐Kun Seo, Jeffrey L. Thorne

The paper evaluates character recoding schemes for phylogenetic analysis using a likelihood framework to assess their impact on evolutionary information.

DOI 10.1101/2025.10.15.682473

statistical modelphylogenetics / evolution

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