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2020 | OriginalPaper | Buchkapitel

A Stochastic Automata Network Description for Spatial DNA-Methylation Models

verfasst von : Alexander Lück, Verena Wolf

Erschienen in: Measurement, Modelling and Evaluation of Computing Systems

Verlag: Springer International Publishing

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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.

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Vorheriges Kapitel Concurrent MDPs with Finite Markovian Policies

Nächstes Kapitel An ns-3 Model for Multipath Communication with Terrestrial and Satellite Links

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Titel: A Stochastic Automata Network Description for Spatial DNA-Methylation Models
verfasst von: Alexander Lück
Verena Wolf
Verlag: Springer International Publishing
Buch: Measurement, Modelling and Evaluation of Computing Systems
Print ISBN: 978-3-030-43023-8

Electronic ISBN: 978-3-030-43024-5

Copyright-Jahr: 2020
DOI: https://doi.org/10.1007/978-3-030-43024-5_4

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