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- W2794571113 abstract "Computational methods are needed to combine diverse type of genome-wide data in a meaningful manner. Based on the kernel embedding of conditional probability distributions, a new measure for inferring the degree of association between two multivariate data sources is introduced. We analyze the performance of the proposed measure to integrate mRNA expression, DNA methylation and miRNA expression data." @default.
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- W2794571113 date "2018-01-01" @default.
- W2794571113 modified "2023-10-15" @default.
- W2794571113 title "Kernel Conditional Embeddings for Associating Omic Data Types" @default.
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- W2794571113 doi "https://doi.org/10.1007/978-3-319-78723-7_43" @default.
- W2794571113 hasPublicationYear "2018" @default.
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