Please use this identifier to cite or link to this item: doi:10.22028/D291-29428
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Title: A Stochastic Model for the Formation of Spatial Methylation Patterns
Author(s): Lück, Alexander
Giehr, Peter Pascal
Walter, Jörn Erik
Wolf, Verena
Editor(s): Feret, Jérôme
Koeppl, Heinz
Language: English
Title: Computational Methods in Systems Biology : 15th International Conference
Startpage: 160
Endpage: 178
Publisher/Platform: Springer
Year of Publication: 2017
Place of publication: Cham
Title of the Conference: CMSB 2017
Place of the conference: Darmstadt, Germany
Publikation type: Conference Paper
Abstract: DNA methylation is an epigenetic mechanism whose important role in development has been widely recognized. This epigenetic modification results in heritable changes in gene expression not encoded by the DNA sequence. The underlying mechanisms controlling DNA methylation are only partly understood and recently different 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 dependencies. We perform numerical analysis of the HMMs applied to bisulfite sequencing measurements and accurately predict wild-type data. In addition, we find evidence that the enzymes’ activities depend on the left 5’ neighborhood but not on the right 3’ neighborhood.
DOI of the first publication: 10.1007/978-3-319-67471-1_10
URL of the first publication: https://link.springer.com/chapter/10.1007/978-3-319-67471-1_10
Link to this record: hdl:20.500.11880/27886
http://dx.doi.org/10.22028/D291-29428
ISBN: 978-3-319-67471-1
978-3-319-67470-4
Date of registration: 25-Sep-2019
Notes: Lecture notes in computer science ; volume 10545
Faculty: NT - Naturwissenschaftlich- Technische Fakultät
Department: NT - Biowissenschaften
Professorship: NT - Prof. Dr. Jörn Walter
Collections:UniBib – Die Universitätsbibliographie

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