📝 Original Info
- Title: The Structure and Dynamics of Gene Regulation Networks
- ArXiv ID: 0802.1989
- Date: 2008-02-15
- Authors: Researchers from original ArXiv paper
📝 Abstract
The structure and dynamics of a typical biological system are complex due to strong and inhomogeneous interactions between its constituents. The investigation of such systems with classical mathematical tools, such as differential equations for their dynamics, is not always suitable. The graph theoretical models may serve as a rough but powerful tool in such cases. In this thesis, I first consider the network modeling for the representation of the biological systems. Both the topological and dynamical investigation tools are developed and applied to the various model networks. In particular, the attractor features' scaling with system size and distributions are explored for model networks. Moreover, the theoretical robustness expressions are discussed and computational studies are done for confirmation. The main biological research in this thesis is to investigate the transcriptional regulation of gene expression with synchronously and deterministically updated Boolean network models. I explore the attractor structure and the robustness of the known interaction network of the yeast, Saccharomyces Cerevisiae and compare with the model networks. Furthermore, I discuss a recent model claiming a possible root to the topology of the yeast's gene regulation network and investigate this model dynamically. The thesis also included another study which investigates a relation between folding kinetics with a new network representation, namely, the incompatibility network of a protein's native structure. I showed that the conventional topological aspects of these networks are not statistically correlated with the phi-values, for the limited data that is available.
💡 Deep Analysis
Deep Dive into The Structure and Dynamics of Gene Regulation Networks.
The structure and dynamics of a typical biological system are complex due to strong and inhomogeneous interactions between its constituents. The investigation of such systems with classical mathematical tools, such as differential equations for their dynamics, is not always suitable. The graph theoretical models may serve as a rough but powerful tool in such cases. In this thesis, I first consider the network modeling for the representation of the biological systems. Both the topological and dynamical investigation tools are developed and applied to the various model networks. In particular, the attractor features’ scaling with system size and distributions are explored for model networks. Moreover, the theoretical robustness expressions are discussed and computational studies are done for confirmation. The main biological research in this thesis is to investigate the transcriptional regulation of gene expression with synchronously and deterministically updated Boolean network models.
📄 Full Content
arXiv:0802.1989v1 [q-bio.MN] 14 Feb 2008
THE STRUCTURE AND DYNAMICS OF
GENE REGULATION NETWORKS
by
Murat Tu˘grul
A Thesis Submitted to the
Graduate School of Sciences and Engineering
in Partial Fulfillment of the Requirements for
the Degree of
Master of Science
in
Computational Sciences & Engineering
Ko¸c University
December, 2007
Ko¸c University
Graduate School of Sciences and Engineering
This is to certify that I have examined this copy of a master’s thesis by
Murat Tu˘grul
and have found that it is complete and satisfactory in all respects,
and that any and all revisions required by the final
examining committee have been made.
Committee Members:
Assist. Prof. Alkan Kabak¸cıo˘glu
Assist. Prof. Deniz Y¨uret
Assoc. Prof. Attila G¨ursoy
Date:
To Peace
iii
ABSTRACT
The structure and dynamics of a typical biological system are complex due to strong
and inhomogeneous interactions between its constituents. The investigation of such systems
with classical mathematical tools, such as differential equations for their dynamics, is not
always suitable. The graph theoretical models may serve as a rough but powerful tool in
such cases.
In this thesis, I first consider the network modeling for the representation of the biological
systems. Both the topological and dynamical investigation tools are developed and applied
to the various model networks. In particular, the attractor features’ scaling with system
size and distributions are explored for model networks. Moreover, the theoretical robustness
expressions are discussed and computational studies are done for confirmation.
The main biological research in this thesis is to investigate the transcriptional regulation
of gene expression with synchronously and deterministically updated Boolean network mod-
els. I explore the attractor structure and the robustness of the known interaction network of
the yeast, Saccharomyces Cerevisiae and compare with the model networks. Furthermore, I
discuss a recent model claiming a possible root to the topology of the yeast’s gene regulation
network and investigate this model dynamically.
The thesis also included another study which investigates a relation between folding ki-
netics with a new network representation, namely, the incompatibility network of a protein’s
native structure. I showed that the conventional topological aspects of these networks are
not statistically correlated with the phi-values, for the limited data that is available.
iv
¨OZETC¸ E
Tipik bir biyolojik sistemin yapısı ve dinami˘gi, ¨ogelerinin birbirleri ile homojen olmayan
ve g¨u¸cl¨u etkile¸simleri sebebiyle karma¸sıktır. Dinamik incelemelerde kullanılan t¨urevli den-
klemler gibi klasik diyebilece˘gimiz matematiksel y¨ontemler, bu t¨ur karma¸sık sistemlerin
incelenmesinde her zaman uygun olmayabilir. C¸izge kuramsal modeller ise daha y¨uzeysel
olsa da bu t¨ur sistemlerin incelenmesi i¸cin daha etkili bir y¨ontem olabilir.
Bu tezde, ilk olarak biyolojik sistemlerin sunumu i¸cin a˘g modellemesi ele aldım. Topolo-
jik ve dinamik inceleme ara¸cları geli¸stirilip ¸ce¸sitli model a˘glara uyarlandı. ¨Ozelde, model
a˘glar i¸cin ¸cekici ¨ozelliklerinin sistem b¨uy¨ukl¨u˘g¨u ile ¨ol¸ceklenmesi ve da˘gılımları incelendi.
Ayrıca, kuramsal dayanıklılık ifadeleri tartı¸sıllıp ve hesaplamalı olarak do˘grulukları sınandı.
Bu tezdeki ana biyoloji ara¸stırması, transkripsiyonel gen ifadesinin d¨uzenlenmesinin
e¸szamanlı ve deterministik g¨uncellenen Boolyan a˘g modeli ile incelenmesi olmu¸stur. Etk-
ile¸sim a˘gı bilinen maya, Saccharomices Cerevisiae’nın ¸cekici yapısını ve dayanıklılı˘gını in-
celedim ve model a˘glar ile kar¸sıla¸stırdım.
Ayrıca, mayanın gen ifadesi a˘gının topolojik
muhtemel temellerini irdeleyen yeni bir modeli tartı¸sdım ve bu modeli dinamik olarak in-
celedim.
Bu tezde ayrıca bir ba¸ska a˘g modellenmesi olan; asıl protein yapısından elde edilen
ba˘gda¸smaz (incompatibility) a˘g ile protein kineti˘ginin incelenmesi yer almaktadır. Elim-
izdeki sınırlı veri ile yapılan sınamalarda geleneksel olarak kullanılan belirli topolojik ¨ozellikler
ile fi-de˘gerleri arasında ba˘gıntı olmadı˘gını g¨osterdim.
v
ACKNOWLEDGMENTS
First of all, I would like to express my gratidute to my advisor, Assist. Prof. Alkan
Kabak¸cıo˘glu, whose understanding, patience and help added considerably to my graduate
experience. I would like to thank other members of my committee Assist. Prof. Deniz Y¨uret
and Assoc. Prof. Attila G¨ursoy for critical readings of this thesis and for their valuable
comments.
A special thank goes to Osman Nuri Yo˘gurt¸cu for his effort in reading and
critiques. I would like to thank Elif M¨ujen S¸encan for being near me during this master
period. Lastly, I would like to thank all my friends, professors, students, workers at Ko¸c
University and the people of Sarıyer.
vi
TABLE OF CONTENTS
List of Tables
ix
List of Figures
x
Prologue
xii
Chapter 1:
Introduction
1
Chapter 2:
Network Modeling
5
2.1
Graph Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . .
…(Full text truncated)…
Reference
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