https://www.selleckchem.com/products/ml198.html
Integrative multi-feature fusion analysis on biomedical data has gained much attention recently. In breast cancer, existing studies have demonstrated that combining genomic mRNA data and DNA methylation data can better stratify can-cer patients with distinct prognosis than using single signature. However, those ex-isting methods are simply combining these gene features in series and have ignored the correlations between separate omics dimensions over time. In the present study, we propose an adaptive multi-task learning method, which comb
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