Recent advances in computational epigenetics

Ruskin, Heather J.; Barat, Ana

doi:10.2147/agg.s115524

Cited by 6 publications

(3 citation statements)

References 129 publications

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“…This mechanism plays an important role in human development and disease, primarily by regulating gene expression. 1 Because of the modifiable nature of epigenetic influence, research into DNA methylation has heralded a new era in the elusive search for the route by which the external world might “get under the skin.” 2 By its very nature, this question spans multiple disciplines; geneticists, 3 biologists, 4 computational scientists, 5 neuroscientists, 6 social scientists, 7 and philosophers 8 have been drawn to massive new data about the epigenome with an eye toward how it might explain health, disease, and our very nature. The promise of the epigenetics revolution has been sweeping.…”

Section: Introductionmentioning

confidence: 99%

Patterns of Reliability: Assessing the Reproducibility and Integrity of DNA Methylation Measurement

et al. 2020

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SUMMARY DNA methylation plays an important role in both normal human development and risk of disease. The most utilized method of assessing DNA methylation uses BeadChips, generating an epigenome-wide “snapshot” of >450,000 observations (probe measurements) per assay. However, the reliability of each of these measurements is not equal, and little consideration is paid to consequences for research. We correlated repeat measurements of the same DNA samples using the Illumina HumanMethylation450K and the Infinium MethylationEPIC BeadChips in 350 blood DNA samples. Probes that were reliably measured were more heritable and showed consistent associations with environmental exposures, gene expression, and greater cross-tissue concordance. Unreliable probes were less replicable and generated an unknown volume of false negatives. This serves as a lesson for working with DNA methylation data, but the lessons are equally applicable to working with other data: as we advance toward generating increasingly greater volumes of data, failure to document reliability risks harming reproducibility.

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Section: Introductionmentioning

confidence: 99%

Patterns of Reliability: Assessing the Reproducibility and Integrity of DNA Methylation Measurement

et al. 2020

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“…This field has been driven by the rapid, extensive progress in methods for generating experimental data [20]. A review of computational methods and implications is covered in [20], and more recently in [21]. Notably, the update of [15] to [22] has an additional chapter devoted to this topic, demonstrating the increase in significance of this area of research in the last ten years.…”

Section: Epigenetic Computational Modelsmentioning

confidence: 99%

“…These models allow researchers to better understand the processes from a mathematical and theoretical point of view. This is an important step, because the inability of gene factors to explain how phenotypic changes occur has become evident, despite ample data [21]. For example, [24] describes an abstract stochastic model that represents the orchestration of interplay among transcription regulation, histone modification, and DNA methylation in somatic cell reprogramming.…”

Section: Epigenetic Computational Modelsmentioning

confidence: 99%

An epigenetic modeling approach for adaptive prognostics of engineered systems

Seale¹,

Garcia-Reyero²,

Salter³

et al. 2021

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Prognostics and health management (PHM) frameworks are widely used in engineered systems, such as manufacturing equipment, aircraft, and vehicles, to improve reliability, maintainability, and safety. Prognostic information for impending failures and remaining useful life is essential to inform decision-making by enabling cost versus risk estimates of maintenance actions. These estimates are generally provided by physics-based or data-driven models developed on historical information. Although current models provide some predictive capabilities, the ability to represent individualized dynamic factors that affect system health is limited. To address these shortcomings, we examine the biological phenomenon of epigenetics. Epigenetics provides insight into how environmental factors affect genetic expression in an organism, providing system health information that can be useful for predictions of future state. The means by which environmental factors influence epigenetic modifications leading to observable traits can be correlated to circumstances affecting system health. In this paper, we investigate the general parallels between the biological effects of epigenetic changes on cellular DNA to the influences leading to either system degradation and compromise, or improved system health. We also review a variety of epigenetic computational models and concepts, and present a general modeling framework to support adaptive system prognostics.

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