Author

Emanuele Saitto

University of MilanORCID 0000-0001-7410-779XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Research Focus:protein design· 1 Assay:protein sequence· 1 Approach:statistical model· 1

Frequent Co-Authors

Alberto PaccanaroiD· 2 shared Elena CasiraghiiD· 2 shared Giorgio ValentiniiD· 2 shared Aldo GaleanoiD· 1 shared Dario MalchiodiiD· 1 shared Emanuele CavalleriiD· 1 shared M. NicoliniiD· 1 shared Marco MesitiiD· 1 shared

Activity by Year

2024-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Alberto PaccanaroORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintSep 22, 2025

AI methods and biologically informed data curation enable accurate RNA m5C prediction

Emanuele Saitto, Elena Casiraghi, Alberto Paccanaro, Giorgio Valentini

The paper trains AI models to predict RNA m5C sites using a curated dataset, achieving high accuracy and revealing the importance of data quality and biological validation.

DOI 10.1101/2025.09.22.677824

bulk RNA-seqdeep learning

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BioinformaticsbioRxivPreprintAug 10, 2024

Fine-tuning of conditional Transformers for the generation of functionally characterized enzymes

M. Nicolini, Emanuele Saitto, Ruben Emilio Jimenez Franco…·Giorgio Valentini

This paper introduces Finenzyme, a Protein Language Model that improves EC category prediction through fine-tuning, generating functionally similar enzymes with preserved structure and function.

1 citation

protein sequencedeep learning

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