Please use this identifier to cite or link to this item: doi:10.22028/D291-31066
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Title: A Stochastic Automata Network Description for Spatial DNA-Methylation Models
Author(s): Lück, Alexander
Wolf, Verena
Editor(s): Hermanns, Holger
Language: English
Title: Measurement, Modelling and Evaluation of Computing Systems : 20th International GI/ITG Conference
Startpage: 54
Endpage: 64
Publisher/Platform: Springer
Year of Publication: 2020
Place of publication: Cham
Title of the Conference: MMB 2020
Place of the conference: Saarbrücken, Germany
Publikation type: Conference Paper
Abstract: DNA methylation is an important biological mechanism to regulate gene expression and control cell development. Mechanistic modeling has become a popular approach to enhance our understanding of the dynamics of methylation pattern formation in living cells. Recent findings suggest that the methylation state of a cytosine base can be influenced by its DNA neighborhood. Therefore, it is necessary to generalize existing mathematical models that consider only one cytosine and its partner on the opposite DNA-strand (CpG), in order to include such neighborhood dependencies. One approach is to describe the system as a stochastic automata network (SAN) with functional transitions. We show that single-CpG models can successfully be generalized to multiple CpGs using the SAN description and verify the results by comparing them to results from extensive Monte-Carlo simulations.
DOI of the first publication: 10.1007/978-3-030-43024-5_4
URL of the first publication:
Link to this record: hdl:20.500.11880/29207
ISBN: 978-3-030-43024-5
Date of registration: 29-May-2020
Notes: Programming and Software Engineering ; volume 12040
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Informatik
Professorship: MI - Prof. Dr. Verena Wolf
Collections:UniBib – Die Universitätsbibliographie

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