Please use this identifier to cite or link to this item: doi:10.22028/D291-31063
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Title: Hidden Markov Modelling Reveals Neighborhood Dependence of Dnmt3a and 3b Activity
Author(s): Luck, Alexander
Giehr, Peter Pascal
Nordstrom, Karl
Walter, Jörn Erik
Wolf, Verena
Language: English
Title: IEEE ACM transactions on computational biology and bioinformatics
Volume: 16
Issue: 5
Startpage: 1598
Endpage: 1609
Publisher/Platform: IEEE
Year of Publication: 2019
Publikation type: Journal Article
Abstract: DNA methylation is an epigenetic mark whose important role in development has been widely recognized. This epigenetic modification results in heritable information not encoded by the DNA sequence. The underlying mechanisms controlling DNA methylation are only partly understood. Several mechanistic models of enzyme activities responsible for DNA methylation have been proposed. Here, we extend existing Hidden Markov Models (HMMs) for DNA methylation by describing the occurrence of spatial methylation patterns over time and propose several models with different neighborhood dependences. Furthermore, we investigate correlations between the neighborhood dependence and other genomic information. We perform numerical analysis of the HMMs applied to comprehensive hairpin and non-hairpin bisulfite sequencing measurements and accurately predict wild-type data. We find evidence that the activities of Dnmt3a and Dnmt3b responsible for de novo methylation depend on 5' (left) but not on 3' (right) neighboring CpGs in a sequencing string.
DOI of the first publication: 10.1109/TCBB.2019.2910814
URL of the first publication: https://ieeexplore.ieee.org/document/8697108
Link to this record: hdl:20.500.11880/29204
http://dx.doi.org/10.22028/D291-31063
ISSN: 1545-5963
1557-9964
Date of registration: 29-May-2020
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Informatik
Professorship: MI - Prof. Dr. Verena Wolf
Collections:UniBib – Die Universitätsbibliographie

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