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By\ndoing this, it enables us to do the feature selection for\ndifferent blocks, and the selected features can then be further\nused to predict the outcome. For example, in biomedical\napplications, clinical covariates plus different types of omics\ndata such as microbiome, metabolome, mRNA data, methylation\ndata, copy number variation data might be predictive for\npatients outcome such as survival time or response to therapy.\nDifferent types of data could be put in different blocks and\nalong with survival time to fit the model. The fitted model can\nthen be used to predict the survival for the new samples with\nthe corresponding clinical covariates and omics data. 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