A robust kernel machine regression towards biomarker selection in multi-omics datasets of osteoporosis for drug discovery
用于骨质疏松多组学生物标志物筛选与药物发现的稳健核机器回归
Many statistical machine approaches could ultimately highlight novel features of the etiology of complex diseases by analyzing multi-omics data. However, they are sensitive to some deviations in distribution when the observed samples are potentially contaminated with adversarial corrupted outliers (e.g., a fictional data distribution). Likewise, statistical advances lag in supporting comprehensive data-driven analyses of complex multi-omics data integration. We propose a…