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Analysis of gene expression data by systems biology methods [Elektronische Ressource] / presented by Yvonne Koch

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128 pages
Dissertation submitted to the Combined Faculties for the Natural Sciences and for Mathematics of the Ruperto Carola University of Heidelberg, Germany for the degree of Doctor of Natural Sciences presented by Dipl. Inf. Yvonne Koch born in: Ulm, Germany thOral-examination: 5 of April 2011 1 2 Analysis of Gene Expression Data by Systems Biology Methods Referees: PD Dr. Rainer König Prof. Dr. Ursula Kummer 3 4 Eidesstattliche Erklärung Hiermit erkläre ich, Yvonne Koch, an Eides Statt, dass ich die an der Universität Heidel-berg vorgelegte Dissertation selbständig und ohne Benutzung anderer als der angegebe-nen Hilfsmittel angefertigt habe. Die aus fremden Quellen übernommenen Gedanken sind als solche kenntlich gemacht. Die Arbeit wurde bisher in gleicher oder ähnlicher Weise keiner anderen Prüfungsbehör-de vorgelegt und auch nicht veröffentlicht. Heidelberg, den 22. Februar 2011 __________________________ Unterschrift 5 6 Acknowledgements First of all, I would like to thank Professor Dr. Roland Eils who gave me the opportunity to do my PhD in the exciting field of systems biology at the Department of Theoretical Bioinformatics at the German Cancer Research Center. The support and freedom he granted enabled me to conduct a research project of interests. I am grateful to PD Dr.
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Dissertation

submitted to the
Combined Faculties for the Natural Sciences and for Mathematics
of the Ruperto Carola University of Heidelberg, Germany
for the degree of

Doctor of Natural Sciences














presented by

Dipl. Inf. Yvonne Koch
born in: Ulm, Germany
thOral-examination: 5 of April 2011


1
2

Analysis of Gene Expression Data by
Systems Biology Methods


















Referees:
PD Dr. Rainer König
Prof. Dr. Ursula Kummer

3

4 Eidesstattliche Erklärung

Hiermit erkläre ich, Yvonne Koch, an Eides Statt, dass ich die an der Universität Heidel-
berg vorgelegte Dissertation selbständig und ohne Benutzung anderer als der angegebe-
nen Hilfsmittel angefertigt habe. Die aus fremden Quellen übernommenen Gedanken sind
als solche kenntlich gemacht.
Die Arbeit wurde bisher in gleicher oder ähnlicher Weise keiner anderen Prüfungsbehör-
de vorgelegt und auch nicht veröffentlicht.

Heidelberg, den 22. Februar 2011
__________________________
Unterschrift

5
6 Acknowledgements
First of all, I would like to thank Professor Dr. Roland Eils who gave me the opportunity
to do my PhD in the exciting field of systems biology at the Department of Theoretical
Bioinformatics at the German Cancer Research Center. The support and freedom he
granted enabled me to conduct a research project of interests.
I am grateful to PD Dr. Rainer König, who filled in for my first supervisor for his support
and helpful discussion.
Further, I thank Professor Dr. Ursula Kummer for her scientific advice as part of my the-
sis advisory committee (TAC) and for being member of my thesis committee at the Com-
bined Faculties of the Natural Sciences and Mathematics of the University of Heidelberg.
Thanks to Dr. Lars Kaderali, also part of my TAC, for his research advice.
Special thanks go to my supervisor Dr. Benedikt Brors, head of the research group Com-
putational Oncology at the German Cancer Research Center. Work discussions during all
stages of my PhD thesis have been helpful and his support enabled to shape my ideas.
Moreover, breadth and depth of his knowledge have been truly inspiring to me.
Furthermore, I thank Barbara Roider, a biotechnology student, who has been eager to
learn about gene expression analysis and mechanistic modeling during a student project.
Many thanks go to Barbara for her collaboration.
Dr. Leo Neumann, Dr. Hannah Schmidt-Glenewinkel and Dr. Peter Bewerunge were
great colleagues who have been always open to discuss and help me with the basics of
mathematical modeling and statistical analyses in Matlab and R. I am grateful, that I met
them at the German Cancer Research Center.
Further, I would like to thank Esteban Czwan and Dr. Joel Beaudouin for carefully read-
ing the manuscript and for their helpful comments.
I want to express my gratitude to my parents for their constant care and encouragement as
well as to my friends Julia Korte and Karmen Lau for being incredible friends.
Finally, I thank Torsten Franz for his loving support during the past years.


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8 Abstract
Perturbed regulation of programmed cell death (apoptosis) plays a major role in tumor
development. The process of eliminating unwanted and damaged cells by apoptosis is
based on complex molecule interactions. Studies of various diseases generally analyse
patient samples in order to find markers or patterns in the data associated with the disease.
However, for analysing biological processes like apoptosis, the focus of interest is to dis-
cover molecular mechanisms within cells and hence consider a different observational
level. Simulation and analysis of differential equation models aid in elucidating complex
interrelations on a mechanistic level. Nevertheless, interpretation of how molecules
mechanisms give rise to a cellular process is complicated, time consuming and the bottle-
neck of systems biology research.
In order to understand interactions and mechanisms of molecules involved in apoptosis on
a systems level in the context of tumor development, this work combines analysis of pa-
tient data and analysis of molecular interactions. To achieve this aim, two different ap-
proaches were followed.
The first approach analyses gene expression data of different tumor entities for their abil-
ity to undergo cell death in silico by simulation of a mathematical model of apoptosis.
The second approach identifies hypothetical conditions required for apoptosis. To this
end, a novel method for model analysis was developed to reveal multivariate control
mechanisms of model behaviour. The method automatically suggests model components
and their crucial interrelations for a specific system response
Conditions concerning certain apoptotic molecules and molecule relations could be con-
firmed. Moreover, interactions and relations were found, which suggest new hypotheses
how apoptosis as a system is governed by a few molecules in a specific way.


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