The protein and its mRNA

For more info about our services contact : help@bestpfe.com

Table of contents

1 Introduction 
1.1 Motivations
1.2 Approach
1.3 Organization of the manuscript and contributions
2 Introduction (en francais) 
3 Notes on molecular cell biology 
3.1 Escherichia coli
3.2 Growth of E. coli
3.3 Gene expression
3.3.1 Transcription
3.3.2 Translation
3.3.3 mRNA degradation
3.4 Regulation of gene expression in E. coli
4 Modeling genetic regulatory network systems 
4.1 Ordinary differential equation models
4.1.1 Modeling transcription-translation
4.1.2 Quasi-steady-state assumption of mRNA concentration
4.2 Analysis of a genetic bistable switch
4.2.1 Phase plane analysis
4.2.2 Jacobian matrix
4.2.3 Piece-wise affine linear system
4.3 Parameter sensitivity analysis
4.3.1 Local sensitivity analysis
4.3.2 Global sensitivity analysis
4.4 Parameter fitting
5 Reduction and stability analysis of a transcription-translation model of RNA polymerase 35
5.1 Introduction
5.2 The coupled transcription-translation model of RNA polymerase
5.2.1 Description of the model
5.2.2 Full equation
5.3 Time-scale reduction (fast-slow behavior)
5.3.1 Parameter values for the coupled transcription-translation models of RNA polymerase
5.3.2 Separation of the full system into “fast” and “slow” variables
5.4 Verification of the applicability of the Tikhonov’s theorem for the fast subsystems
5.5 Application of the Tikhonov’s theorem
5.6 Dynamical study of the reduced system
5.6.1 Simulations of the full and the reduced system
5.6.2 Equilibria of the reduced system
5.6.3 Stability of equilibria
5.7 Applications to other models
5.8 Comparison with a classical model of RNA polymerase
5.9 System with a variable growth rate
5.10 Conclusion
6 Principal process analysis and its robustness to parameter changes 
6.1 Introduction
6.2 Methodology
6.2.1 Principal process analysis (PPA)
6.2.2 Visualization of process activities
6.2.3 First model reduction
6.2.4 Creation of chains of sub-models
6.2.5 Global sensitivity analysis
6.3 Model description
6.4 Principal process analysis and first reduction
6.5 Creation of sub-models
6.6 Parameter influence
6.7 Conclusion
7 Principal process analysis and reduction of biological models with dif-ferent orders of magnitude 
7.1 Introduction
7.2 Methodology
7.2.1 Principal process analysis and model reduction
7.2.2 Principal process analysis and model reduction based on initial conditions in a rectangle
7.2.3 Possible transitions between domains
7.3 The gene expression model
7.4 Model reduction from an initial condition
7.5 Model reduction in a rectangle
7.6 Conclusion
8 Principal process analysis applied to a model of endocrine toxicity induced by Fluopyram 
8.1 Introduction
8.2 Methodology
8.2.1 Absolute principal process analysis
8.2.2 Visualization of the process activity
8.3 Hierarchical graph
8.4 Model
8.4.1 Blood compartment
8.4.2 Liver compartment
8.4.3 Brain compartment
8.4.4 Thyroid compartment
8.4.5 The data
8.4.6 Different experiments in silico
8.5 Absolute principal process analysis on the experiment 1A
8.6 Absolute principal process analysis on the experiment 2B
8.7 Conclusion and future steps
9 Model and control of the gene expression machinery in E. coli 
9.1 Introduction
9.2 The model
9.2.1 Growth rate
9.3 The effect of IPTG on E. coli growth
9.4 Model analysis with three-level PPA
9.4.1 Methodology
9.4.2 Different applications
9.4.2.1 Nutrient stress condition
9.4.2.2 IPTG stress condition
9.5 Conclusion
10 Single-cell model calibration of growth control experiments in E. coli 
10.1 Introduction
10.2 Model
10.3 Methodology
10.3.1 Data
10.3.2 Extraction of cellular profiles
10.3.3 Calculation of average cell profiles
10.3.4 Calibration of the model
10.4 Results
10.4.1 Cellular profiles
10.4.2 Calibration of the average cell model
10.4.3 Calibration of the single-cell models
10.4.4 Comparison
10.5 Conclusion
11 Conclusion and perspectives
11.1 Classical tools for the analysis and reduction of biological models
11.2 New tools for the analysis and reduction of biological systems
11.3 Design and analysis of the gene expression machinery in E. coli
11.4 Single-cell and average cell calibration of the gene expression machinery control in E. coli