Covering Hierarchical Dirichlet Mixture Models on binary data to enhance genomic stratifications in onco-hematology.

Covering Hierarchical Dirichlet Mixture Models on binary data to enhance genomic stratifications in onco-hematology.

Onco-hematological studies are increasingly adopting statistical mixture models to support the advancement of the genomically-driven classification systems for blood cancer. Targeting enhanced patients stratification based on the sole role of molecular biology attracted much interest and contributes...

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Main Authors: Daniele Dall'Olio, Eric Sträng, Amin T Turki, Jesse M Tettero, Martje Barbus, Renate Schulze-Rath, Javier Martinez Elicegui, Tommaso Matteuzzi, Alessandra Merlotti, Luciana Carota, Claudia Sala, Matteo G Della Porta, Enrico Giampieri, Jesús María Hernández-Rivas, Lars Bullinger, Gastone Castellani, with the HARMONY Healthcare Alliance Consortium
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2024-02-01
Series:PLoS Computational Biology
Online Access:https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1011299&type=printable

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https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1011299&type=printable

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