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ABSTRACT: Background
Epigenetic phenomena are crucial for explaining the phenotypic plasticity seen in the cells of different tissues, developmental stages and diseases, all holding the same DNA sequence. As technology is allowing to retrieve epigenetic information in a genome-wide fashion, massive epigenomic datasets are being accumulated in public repositories. New approaches are required to mine those data to extract useful knowledge. We present here an automatic approach for detecting genomic regions with epigenetic variation patterns across samples related to a grouping of these samples, as a way of detecting regions functionally associated to the phenomenon behind the classification.Results
We show that the regions automatically detected by the method in the whole human genome
SUBMITTER: Pazos F
PROVIDER: S-EPMC6264639 | biostudies-literature | 2018 Nov
REPOSITORIES: biostudies-literature