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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, et al. Multi-omic modelling of inflammatory bowel disease with regularized canonical correlation analysis. PLoS One. 2021. Vol. 16, num. 2, pags. e0246367. ISSN 1932-6203. [consulted: 12 of November of 2026]. Available at: https://hdl.handle.net/2445/194949