Author

Stefano Rebellato

ORCID 0000-0002-8380-5255Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Organism:human· 1 Assay:whole-exome sequencing· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Adriana BalduzziiD· 1 shared Anke Katharina BergmanniD· 1 shared Annika V. Rademacher· 1 shared Carmelo RizzariiD· 1 shared Franco LocatelliiD· 1 shared Giovanni CazzanigaiD· 1 shared Grazia FazioiD· 1 shared Gunnar CarioiD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Adriana BalduzziORCID

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1 paper

Recent·Most cited

clinTALL: machine learning-driven multimodal subtypeclassification and treatment outcome prediction in pediatric T-ALL

Lukas Stoiber, Željko Antić, Stefano Rebellato, Grazia Fazio, Annika V. Rademacher, Lennart Lenk, Franco Locatelli, Adriana Balduzzi, Gunnar Cario, Carmelo Rizzari, Giovanni Cazzaniga, Jiangyan Yu, Anke Katharina Bergmann

clinTALL is a deep learning framework that classifies pediatric T-ALL subtypes and predicts treatment outcomes using multimodal data, achieving high accuracy and concordance indices.

Genome Medicine · Jul 22, 2026Peer-reviewedBioinformatics