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Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach
Journal article   Open access  Peer reviewed

Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach

M Muksitul Haque, Lawrence B Holder and Michael K Skinner
PloS one, Vol.10(11), pp.e0142274-e0142274
2015
Handle:
https://hdl.handle.net/2376/110589
PMCID: PMC4646459
PMID: 26571271
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url
https://doi.org/10.1371/journal.pone.0142274View
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Abstract

Epigenesis, Genetic Databases, Genetic Granulosa Cells - drug effects Granulosa Cells - metabolism Sertoli Cells - drug effects DDT - toxicity DNA Methylation Sertoli Cells - metabolism Computational Biology - methods Genetic Predisposition to Disease Genome-Wide Association Study Reproducibility of Results Environmental Exposure Spermatozoa - drug effects Sequence Analysis, DNA Chromosomes - ultrastructure Methoxychlor - toxicity Bayes Theorem CpG Islands Cluster Analysis Machine Learning Phenotype Mutation

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