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Article

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Accepted version

Publication date

2018

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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/156044

Kernel conditional Embeddings for associating omic data types

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https://doi.org/10.1007/978-3-319-78723-7_43

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.

Subject

Bioinformàtica, Genòmica

Subject (English)

Bioinformatics, Genomics

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Articles publicats en revistes (Genètica, Microbiologia i Estadística)

Citation

REVERTER COMES, Ferran, VEGAS LOZANO, Esteban and OLLER I SALA, Josep Maria. Kernel conditional Embeddings for associating omic data types. Lecture Notes in Computer Science. 2018. Vol. 10813  LNBI, num. 501-510. ISSN 0302-9743. [consulted: 9 of June of 2026]. Available at: https://hdl.handle.net/2445/156044

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