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cc-by (c) Revilla, Lluís et al., 2021
Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/194949

Multi-omic modelling of inflammatory bowel disease with regularized canonical correlation analysis

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Personalized medicine requires finding relationships between variables that influence a patient's phenotype and predicting an outcome. Sparse generalized canonical correlation analysis identifies relationships between different groups of variables. This method requires establishing a model of the expected interaction between those variables. Describing these interactions is challenging when the relationship is unknown or when there is no pre-established hypothesis. Thus, our aim was to develop a method to find the relationships between microbiome and host transcriptome data and the relevant clinical variables in a complex disease, such as Crohn's disease.

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REVILLA, Lluís, MAYORGAS, Aida, CORRALIZA MÁRQUEZ, Ana maria, MASAMUNT, Maria carme, METWALY, Amira, HALLER, Dirk, TRISTÁN, Eva, CARRASCO GARCÍA, Anna, ESTEVE I COMAS, Maria, PANÉS DÍAZ, Julià, RICART, Elena, LOZANO SALVATELLA, Juan josé, SALAS MARTÍNEZ, Azucena. Multi-omic modelling of inflammatory bowel disease with regularized canonical correlation analysis. _PLoS One_. 2021. Vol. 16, núm. 2, pàgs. e0246367. [consulta: 11 de abril de 2026]. ISSN: 1932-6203. [Disponible a: https://hdl.handle.net/2445/194949]

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