scholarly journals A Stochastic Model for the Formation of Spatial Methylation Patterns

2017 ◽  
pp. 160-178 ◽  
Author(s):  
Alexander Lück ◽  
Pascal Giehr ◽  
Jörn Walter ◽  
Verena Wolf
Keyword(s):  
Stochastic Model ◽  
Methylation Patterns

Maintenance and regulation of DNA methylation patterns in mammals

2005 ◽  
Vol 83 (4) ◽  
pp. 438-448 ◽  
Author(s):  
Zhao-xia Chen ◽  
Arthur D Riggs
Keyword(s):  
Dna Methylation ◽  
Gene Regulation ◽  
Stochastic Model ◽  
Dna Methyltransferase ◽  
Recent Progress ◽  
Molecular Mechanisms ◽  
Normal Development ◽  
Epigenetic Information ◽  
Methylation Patterns ◽  
Maintenance Methylation

Proper establishment and faithful maintenance of epigenetic information is crucial for the correct development of complex organisms. For mammals, it is now accepted that DNA methylation is an important mechanism for establishing stable heritable epigenetic marks. The distribution of methylation in the genome is not random, and patterns of methylated and unmethylated DNA are well regulated during normal development. The molecular mechanisms by which methylation patterns are established and maintained are complex and just beginning to be understood. In this review, we summarize recent progress in understanding the regulation of mammalian DNA methylation patterns, with an emphasis on the emerging roles of several protein and possible RNA factors. We also revisit the stochastic model of maintenance methylation and discuss its implications for epigenetic fidelity and gene regulation.Key words: Epigenetics, epigenetic fidelity, DNA methyltransferase, DNA demethylase, gene regulation.

A Fruitful Stochastic Model

1964 ◽  
Vol 9 (7) ◽  
pp. 273-276
Author(s):  
ANATOL RAPOPORT
Keyword(s):  
Stochastic Model

A Stochastic Model for Evolution of Altruistic Genes

1996 ◽  
Vol 6 (4) ◽  
pp. 445-453 ◽  
Author(s):  
Roberta Donato
Keyword(s):  
Stochastic Model

A Stochastic Model for the Inheritance of the Cancer Proneness Phenotype

1987 ◽  
Vol 26 (03) ◽  
pp. 117-123
Author(s):  
P. Tautu ◽  
G. Wagner
Keyword(s):  
Stochastic Model ◽  
Gaussian Process ◽  
Covariance Function ◽  
Neoplastic Disease ◽  
Disease Phenotype ◽  
Probabilistic Representation ◽  
Temporal Behaviour ◽  
Continuous Trait ◽  
Continuous Parameter ◽  
Level Zero

SummaryA continuous parameter, stationary Gaussian process is introduced as a first approach to the probabilistic representation of the phenotype inheritance process. With some specific assumptions about the components of the covariance function, it may describe the temporal behaviour of the “cancer-proneness phenotype” (CPF) as a quantitative continuous trait. Upcrossing a fixed level (“threshold”) u and reaching level zero are the extremes of the Gaussian process considered; it is assumed that they might be interpreted as the transformation of CPF into a “neoplastic disease phenotype” or as the non-proneness to cancer, respectively.

Vestibular Schwannoma Clinical Phenotypes Are Associated with Differential Methylation Patterns

2020 ◽  
Author(s):  
Avital Perry ◽  
Christopher S. Graffeo ◽  
Lucas P. Carlstrom ◽  
Amanda Munoz Casabella ◽  
Matthew L. Carlson ◽  
...  
Keyword(s):  
Vestibular Schwannoma ◽  
Differential Methylation ◽  
Clinical Phenotypes ◽  
Methylation Patterns

Stochastic Model of Traffic Jam and Traffic Signal Control

2011 ◽  
Vol 131 (2) ◽  
pp. 303-310
Author(s):  
Ji-Sun Shin ◽  
Cheng-You Cui ◽  
Tae-Hong Lee ◽  
Hee-hyol Lee
Keyword(s):  
Stochastic Model ◽  
Traffic Signal ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Traffic Jam
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