Author

Dario Di Bari

Institut d'Investigació Biomédica de BellvitgeORCID 0009-0009-4625-8190Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Assay:Hi-C· 1 Assay:imaging· 1 Organism:mouse· 1 Approach:statistical model· 1

Frequent Co-Authors

Elena VitaliiD· 1 shared Eva Mejía-RamíreziD· 1 shared Maria Carolina FlorianiD· 1 shared Pablo Iáñez PicazoiD· 1 shared Paula PetroneiD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

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5 top collaborators · 10 mutual co-author links

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1 shared paperBioinformatics

Elena VitaliORCID

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1 paper

Recent·Most cited

BioinformaticsbioRxivPreprintDec 15, 2025

Deep learning predicts haematopoietic stem cell ageing from 3D chromatin images

Pablo Iáñez Picazo, Eva Mejía-Ramírez, Dario Di Bari…·Paula Petrone

This paper develops a deep learning model to predict haematopoietic stem cell ageing from 3D chromatin images, achieving an AUROC of 0.77 and identifying key chromatin features as predictive markers.

1 citation

mouseHi-C

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