Description 
1 online resource 
Contents 
Intro; 1 Introduction; 1.1 Motivation; 1.2 Contributions and outline of the thesis; 2 Background; 2.1 Biological fundamentals of gene regulation; 2.2 Mathematical modeling of gene regulation networks; 2.3 Measurement techniques; 3 Identification of Boolean or discrete models of gene regulation networks; 3.1 Introduction and problem statement; 3.2 Polynomial representation of discrete functions; 3.3 Reformulation of the identification problem as a linear program; 3.4 Reduced order representation and robust estimation of unate Boolean functions; 3.5 Application examples 

3.6 Summary and discussion4 Analysis of multistability and multistability robustness; 4.1 Introduction and problem statement; 4.2 Modeling framework and preliminaries; 4.3 A combinatorial approach for the validation of multistability in gene regulation networks; 4.4 Steady state robustness analysis and model discrimination; 4.5 Application examples; 4.6 Summary and discussion; 5 Control of Boolean models of gene regulation networks; 5.1 Introduction and problem statement; 5.2 Representation of Boolean networks as a discrete event system; 5.3 Application example; 5.4 Summary and discussion 

6 Conclusion6.1 Summary; 6.2 Outlook; Appendix 
Summary 
Long description: A systems biological approach towards cellular networks promises a better understanding of how these systems work. The development of mathematical models is however inherently complicated, as the involved molecules and their interactions are mostly difficult to measure. Focusing on gene regulation networks, this work therefore intends to provide systems theoretic tools that support the process of model development and analysis in presence of such incomplete knowledge. The contributions are threefold. First, the problem of identifying interconnections between genes from noisy data is addressed. Existing solutions formulated in a discrete framework are reviewed and simplified significantly with the help of tools from convex optimization theory. Second, a novel method for model verification and discrimination is introduced. It is based on concepts from robust control theory and allows to quantify the capability of a model to reproduce experimentally observed stationary behaviors. As the proposed formalism only requires a vague knowledge about the interactions between the molecules, the method is intended to test and compare early modeling hypotheses. Third, the problem of controlling gene regulation networks in presence of qualitative information only is studied. Methods from discrete event systems theory are adapted to obtain stimulation strategies that will steer the network toward a desired attractor. The benefits of all contributions are illustrated with examples in the individual chapters 
Bibliography 
Includes bibliographical references (pages 117125) 
Notes 
In English. Some information on title page, title page verso, and part of introduction, in German 
Subject 
Gene regulatory networks.


Gene Regulatory Networks


Gene regulatory networks

Form 
Electronic book

LC no. 
2016498388 
ISBN 
9783832591427 

3832591427 
