Author

Ieva Pudžiuvelytė

SIB Swiss Institute of BioinformaticsORCID 0009-0004-0600-590XUnclaimed 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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Assay:protein sequence· 2 Research Focus:protein structure prediction· 2 Research Focus:benchmarking· 1 Approach:contrastive learning· 1 Approach:deep learning· 1 Research Focus:sequence-to-function modeling· 1

Frequent Co-Authors

Andrew Mark WaterhouseiD· 1 shared Darius KazlauskasiD· 1 shared Eglė GodliauskaitėiD· 1 shared Florian PommereningiD· 1 shared Gabriel StuderiD· 1 shared Gerardo TaurielloiD· 1 shared Giedrius GasiūnasiD· 1 shared Janani DurairajiD· 1 shared

Activity by Year

2024-2025 · peak 1/yr

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10 top collaborators · 20 mutual co-author links

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1 shared paperBioinformatics

Andrew Mark WaterhouseORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintNov 27, 2025

Rewriting protein alphabets with language models

Lorenzo Pantolini, Gabriel Studer, Laura Engist…·Janani Durairaj

This paper introduces a new 20-letter alphabet, TEA, derived from protein language models, enabling efficient homology searches comparable to structure-based methods without structural data.

4 citations

protein sequencecontrastive learning

𝕏 PostBluesky

BioinformaticsBioinformaticsPeer-reviewedMar 20, 2024

TemStaPro: protein thermostability prediction using sequence representations from protein language models

Ieva Pudžiuvelytė, Kliment Olechnovič, Eglė Godliauskaitė…·Darius Kazlauskas

TemStaPro predicts protein thermostability using sequence embeddings from protein language models, showing good agreement with experimental data.

65 citationstop 1%

protein sequencedeep learning

𝕏 PostBluesky