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MPI-INF D3 Publications :: Thesis :: Bock, Christoph


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Thesis - Doctoral dissertation | @PhdThesis | Doktorarbeit


Author
Author(s)*:Bock, Christoph
BibTeX citekey*:Bock2008b
Language:English

Title, School
Title*:Computational Epigenetics - Bioinformatic methods for epigenome prediction, DNA methylation mapping and cancer epigenetics
School:Universität des Saarlandes
Type of Thesis*:Doctoral dissertation
Month:October
Year:2008


Note, Abstract, Copyright
LaTeX Abstract:Epigenetic research aims to understand heritable gene regulation that is not directly encoded in the DNA sequence. Epigenetic mechanisms such as DNA methylation and histone modifi-cations modulate the packaging of the DNA in the nucleus and thereby influence gene expres-sion. Patterns of epigenetic information are faithfully propagated over multiple cell divisions, which makes epigenetic gene regulation a key mechanism for cellular differentiation and cell fate decisions. In addition, incomplete erasure of epigenetic information can lead to complex patterns of non-Mendelian inheritance. Stochastic and environment-induced epigenetic de-fects are known to play a major role in cancer and ageing, and they may also contribute to mental disorders and autoimmune diseases.

Recent technical advances – such as the development of the ChIP-on-chip and ChIP-seq protocols for genome-wide mapping of epigenetic information – have started to convert epi-genetic research into a high-throughput endeavor, to which bioinformatics is expected to make significant contributions. This thesis describes computational work at the intersection of epi-genetics and genome research, aiming to address the bioinformatic challenges posed by the human epi¬genome. While its methods are carried over and adapted from bioinformatics and related fields (including data mining, machine learning, statistics, algorithms, optimization, software engineering and databases), its overarching goal is to contribute to epigenetic re-search, both directly through analyzing and modeling of epigenetic information, and indirectly through the development of practically useful methods and software toolkits.
This thesis is broadly structured into four parts. The first part gives a brief introduction into epigenetic regulation and inheritance, and reviews the emerging field of computational epigenetics. The second part addresses the question of genome-epigenome interactions using machine learning methods. It is shown that accurate predictions of DNA methylation and oth-er epigenetic modifications can be derived from the genomic DNA sequence. Based on this finding, the EpiGRAPH web service for epigenome analysis and prediction is described, and methods for refined annotation of CpG islands in the human genome are proposed. The third part is dedicated to large-scale analysis of DNA methylation, which is the best-known epige-netic phenomenon. The BiQ Analyzer software toolkit is presented, together with a bioinfor-matic analysis of the “National Methylome Project for Chromosome 21” dataset, for which BiQ Analyzer had played an enabling role. This part concludes with statistical modeling of DNA methylation variation and an analysis of its implications for DNA methylation mapping in a large number of human individuals. The fourth part describes two pilot projects applying the bioinformatic concepts of this thesis to cancer epigenetics. First, genome-scale datasets are probed for evidence of a link between DNA methylation and Polycomb binding, which is believed to play a role in epigenetic deregulation of cancer cells. Second, a biomarker that tests for cancer-specific DNA methylation is optimized and validated for use in clinical set-tings.
Arguably the most interesting result of this thesis is the unexpectedly high correlation be-tween genome and epigenome that was found by several methods and based on multiple epi-genome datasets. This finding suggests that the role of the genome for epigenetic regulation has been underappreciated, and it underlines the importance of integrated analysis of genome and epigenome. With the EpiGRAPH web service for (epi-) genome analysis and prediction, a research tool is provided to facilitate further investigation of this striking interaction.

Download Access Level:Internal

Referees, Status, Dates
1. Referee:Prof. Dr. Thomas Lengauer, Ph.D.
2. Referee:Prof. Dr. Jörn Walter
Status:Completed
Date Kolloquium:17 December 2008

Correlation
MPG Unit:Max-Planck-Institut für Informatik
MPG Subunit:Computational Biology and Applied Algorithmics
Audience:popular
Appearance:MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort


BibTeX Entry:
@PHDTHESIS{Bock2008b,
AUTHOR = {Bock, Christoph},
TITLE = {Computational Epigenetics - Bioinformatic methods for epigenome prediction, DNA methylation mapping and cancer epigenetics},
SCHOOL = {Universit{\"a}t des Saarlandes},
YEAR = {2008},
TYPE = {Doctoral dissertation}
MONTH = {October},
}



Entry last modified by Christoph Bock, 03/13/2009
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Editor(s)
Christoph Bock
Created
12/17/2008 11:11:12 PM
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Editor(s)
Christoph Bock
Christoph Bock
Christoph Bock

Edit Dates
03/13/2009 04:57:32 AM
17/12/2008 23:14:29
17/12/2008 23:13:42