Systematic variation is a common issue in metabolomics data analysis.
Th...
Many statistical machine approaches could ultimately highlight novel fea...
In recent years, a comprehensive study of multi-view datasets (e.g.,
mul...
Classification is an important supervised machine learning method, which...
Identifying significant subsets of the genes, gene shaving is an essenti...
In this study, we tested the interaction effect of multimodal datasets u...
Many unsupervised kernel methods rely on the estimation of the kernel
co...
Kernel and Multiple Kernel Canonical Correlation Analysis (CCA) are empl...
In genome-wide interaction studies, to detect gene-gene interactions, mo...
Imaging genetic research has essentially focused on discovering unique a...
To the best of our knowledge, there are no general well-founded robust
m...