International Workshop on Hybrid Systems Biology

Hybrid Systems Biology pp 141-155 | Cite as

Model-Based Whole-Genome Analysis of DNA Methylation Fidelity

  • Christoph Bock
  • Luca Bortolussi
  • Thilo Krüger
  • Linar Mikeev
  • Verena Wolf
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9271)

Abstract

We consider the problem of understanding how DNA methylation fidelity, i.e. the preservation of methylated sites in the genome, varies across the genome and across different cell types. Our approach uses a stochastic model of DNA methylation across generations and trains it using data obtained through next generation sequencing. By training the model locally, i.e. learning its parameters based on observations in a specific genomic region, we can compare how DNA methylation fidelity varies genome-wide. In the paper, we focus on the computational challenges to scale parameter estimation to the whole-genome level, and present two methods to achieve this goal, one based on moment-based approximation and one based on simulation. We extensively tested our methods on synthetic data and on a first batch of experimental data.

Keywords

DNA methylation Epigenomics Branching processes Parameter estimation Next generation sequencing 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Christoph Bock
    • 3
    • 4
    • 5
  • Luca Bortolussi
    • 1
    • 2
  • Thilo Krüger
    • 1
  • Linar Mikeev
    • 1
  • Verena Wolf
    • 1
  1. 1.Modelling and Simulation GroupUniversity of SaarlandSaarbrückenGermany
  2. 2.DMGUniversity of TriesteTriesteItaly
  3. 3.CeMM Research Center for Molecular Medicine of the Austrian Academy of SciencesViennaAustria
  4. 4.Department of Laboratory MedicineMedical University of ViennaViennaAustria
  5. 5.Max Planck Institute for InformaticsSaarbrückenGermany

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