Multimodal Omics Data Integration Using Max Relevance--Max Significance Criterion.

Abstract excerpt

OBJECTIVE: This paper presents a novel supervised regularized canonical correlation analysis, termed as CuRSaR, to extract relevant and significant features from multimodal high dimensional omics datasets. METHODS: The proposed method extracts a new set of features from two multidimensional datasets by maximizing the relevance of extracted features with respect to sample categories and significance among them. It...

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