Author

Andreina Tirabassi

Helmholtz Munich

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Assay:CITE-seq· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:gene regulatory network inference· 1 Approach:graph neural network· 1

Frequent Co-Authors

Annalisa MarsicoiD· 2 shared Artem BaranovskiiiD· 1 shared Charlotte CapitanchikiD· 1 shared Filippo ValleiD· 1 shared Gabriele MalagoliiD· 1 shared Gabrijela DumbovićiD· 1 shared Jernej UleiD· 1 shared Julien GagneuriD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 31 mutual co-author links

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2 shared papersBioinformatics

Annalisa MarsicoORCID

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2 papers

Recent·Most cited

PARNET: A CLIP-SEQ-BASED FOUNDATION MODEL FOR RNA SEQUENCE REPRESENTATION LEARNING

Lambert Moyon, Andreina Tirabassi, Artem Baranovskii, Charlotte Capitanchik, Klara Kuret, Leo Wilkinson, Shubankar Londhe, Gabrijela Dumbović, Julien Gagneur, Jernej Ule, Marc Horlacher, Annalisa Marsico

Parnet is a CLIP-seq-based foundation model for RNA sequence representation learning that outperforms existing methods in binding profile prediction and generalizes across tasks.

bioRxiv · Aug 17, 2026 · PreprintBioinformatics

Integration of single-cell multi-omic data with graph-based topic modelling

Gabriele Malagoli, Filippo Valle, Andreina Tirabassi, Annalisa Marsico, Loredana Martignetti, Michele Caselle, Maria Colomé‐Tatché

This paper introduces a graph-based topic modelling method for single-cell multi-omic data, showing improved performance in clustering and biological interpretation.

bioRxiv · Feb 26, 2026 · PreprintBioinformatics