Author

Leandro Ezequiel Di Persia

Consejo Nacional de Investigaciones Científicas y TécnicasORCID 0000-0002-0331-6989Unclaimed 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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Approach:deep learning· 2 Research Focus:benchmarking· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1

Frequent Co-Authors

Diego Humberto MiloneiD· 2 shared Georgina S. StegmayeriD· 2 shared Leandro A. BugnoniD· 2 shared Emilio FenoyiD· 1 shared Federico ArieliD· 1 shared Guillermo Kulemeyer· 1 shared Jonathan RaadiD· 1 shared Matias F. GerardiD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 35 mutual co-author links

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2 shared papersBioinformatics

Diego Humberto MiloneORCID

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2 papers

Recent·Most cited

Homology-aware cross-validation strategies for generalization assessment in RNA secondary structure prediction

Leandro A. Bugnon, Guillermo Kulemeyer, Matias Gerard, Leandro Ezequiel Di Persia, Georgina S. Stegmayer, Diego Humberto Milone

The paper evaluates cross-validation strategies for RNA secondary structure prediction, showing that current methods bias results and proposing homology-aware strategies for fair comparison.

bioRxiv · Jun 29, 2026 · PreprintBioinformatics

sincFold: end-to-end learning of short- and long-range interactions in RNA secondary structure

Leandro A. Bugnon, Leandro Ezequiel Di Persia, Matias F. Gerard, Jonathan Raad, Santiago Prochetto, Emilio Fenoy, Uciel Chorostecki, Federico Ariel, Georgina S. Stegmayer, Diego Humberto Milone

sincFold is a deep learning model that predicts RNA secondary structure contact matrices from sequences, outperforming existing methods on benchmark datasets.

Briefings in Bioinformatics · May 23, 2024Peer-reviewedBioinformatics