Preface of the First Edition |
Preface of the Second Edition |
Networks in Biological Cells / 1: |
Some Basics About Networks / 1.1: |
Random Networks / 1.1.1: |
Small-World Phenomenon / 1.1.2: |
Scale-Free Networks / 1.1.3: |
Biological Background / 1.2: |
Transcriptional Regulation / 1.2.1: |
Cellular Components / 1.2.2: |
Spatial Organization of Eukaryotic Cells into Compartments / 1.2.3: |
Considered Organisms / 1.2.4: |
Cellular Pathways / 1.3: |
Biochemical Pathways / 1.3.1: |
Enzymatic Reactions / 1.3.2: |
Signal Transduction / 1.3.3: |
Cell Cycle / 1.3.4: |
Ontologies and Databases / 1.4: |
Ontologies / 1.4.1: |
Gene Ontology / 1.4.2: |
Kyoto Encyclopedia of Genes and Genomes / 1.4.3: |
Reactome / 1.4.4: |
Brenda / 1.4.5: |
DAVID / 1.4.6: |
Protein Data Bank / 1.4.7: |
Systems Biology Markup Language / 1.4.8: |
Methods for Cellular Modeling / 1.5: |
Summary / 1.6: |
Problems / 1.7: |
Bibliography |
Structures of Protein Complexes and Subcellular Structures / 2: |
Examples of Protein Complexes / 2.1: |
Principles of Protein-Protein Interactions / 2.1.1: |
Categories of Protein Complexes / 2.1.2: |
Complexome: The Ensemble of Protein Complexes / 2.2: |
Complexome of Saccharomyces cerevisiae / 2.2.1: |
Bacterial Protein Complexomes / 2.2.2: |
Complexome of Human / 2.2.3: |
Experimental Determination of Three-Dimensional Structures of Protein Complexes / 2.3: |
X-ray Crystallography / 2.3.1: |
NMR / 2.3.2: |
Electron Crystallography/Electron Microscopy / 2.3.3: |
Cryo-EM / 2.3.4: |
Immunoelectron Microscopy / 2.3.5: |
Fluorescence Resonance Energy Transfer / 2.3.6: |
Mass Spectroscopy / 2.3.7: |
Density Fitting / 2.4: |
Correlation-Based Density Fitting / 2.4.1: |
Fourier Transformation / 2.5: |
Fourier Series / 2.5.1: |
Continuous Fourier Transform / 2.5.2: |
Discrete Fourier Transform / 2.5.3: |
Convolution Theorem / 2.5.4: |
Fast Fourier Transformation / 2.5.5: |
Advanced Density Fitting / 2.6: |
Laplacian Filter / 2.6.1: |
FFT Protein-Protein Docking / 2.7: |
Protein-Protein Docking Using Geometric Hashing / 2.8: |
Prediction of Assemblies from Pairwise Docking / 2.9: |
CombDock / 2.9.1: |
Multi-LZerD / 2.9.2: |
3D-MOSAIC / 2.9.3: |
Electron Tomography / 2.10: |
Reconstruction of Phantom Cell / 2.10.1: |
Protein Complexes in Mycoplasma pneumonia / 2.10.2: |
Mapping of Crystal Structures into EM Maps / 2.11: |
Analysis of Protein-Protein Binding / 3: |
Modeling by Homology / 3.1: |
Properties of Protein-Protein Interfaces / 3.2: |
Size and Shape / 3.2.1: |
Composition of Binding Interfaces / 3.2.2: |
Hot Spots / 3.2.3: |
Physicochemical Properties of Protein Interfaces / 3.2.4: |
Predicting Binding Affinities of Protein-Protein Complexes / 3.2.5: |
Forces Important for Biomolecular Association / 3.2.6: |
Predicting Protein-Protein Interactions / 3,3: |
Pairing Propensities / 3.3.1: |
Statistical Potentials for Amino Acid Pairs / 3.3.2: |
Conservation at Protein Interfaces / 3.3.3: |
Correlated Mutations at Protein Interfaces / 3.3.4: |
Algorithms on Mathematical Graphs / 3.4: |
Primer on Mathematical Graphs / 4.1: |
A Few Words About Algorithms and Computer Programs / 4.2: |
Implementation of Algorithms / 4.2.1: |
Classes of Algorithms / 4.2.2: |
Data Structures for Graphs / 4.3: |
Dijkstra's Algorithm / 4.4: |
Description of the Algorithm / 4.4.1: |
Pseudocode / 4.4.2: |
Running Time / 4.4.3: |
Minimum Spanning Tree / 4.5: |
Kruskal's Algorithm / 4.5.1: |
Graph Drawing / 4.6: |
Force Directed Layout of Graphs / 4.7: |
Protein-Protein Interaction Networks - Pairwise Connectivity / 5: |
Experimental High-Throughput Methods for Detecting Protein-Protein Interactions / 5.1: |
Gel Electrophoresis / 5.1.1: |
Two-Dimensional Gel Electrophoresis / 5.1.2: |
Affinity Chromatography / 5.1.3: |
Yeast Two-hybrid Screening / 5.1.4: |
Synthetic Lethality / 5.1.5: |
Gene Co expression / 5.1.6: |
Databases for Interaction Networks / 5.1.7: |
Overlap of Interactions / 5.1.8: |
Criteria to Judge the Reliability of Interaction Data / 5.1.9: |
Bioinformatic Prediction of Protein-Protein Interactions / 5.2: |
Analysis of Gene Order / 5.2.1: |
Phylogenetic Profiling/Coevolutionary Profiling / 5.2.2: |
Coevolution / 5.2.2.1: |
Bayesian Networks for Judging the Accuracy of Interactions / 5.3: |
Bayes' Theorem / 5.3.1: |
Bayesian Network / 5.3.2: |
Application of Bayesian Networks to Protein-Protein Interaction Data / 5.3.3: |
Measurement of Reliability "Likelihood Ratio" / 5.3.3.1: |
Prior and Posterior Odds / 5.3.3.2: |
A Worked Example: Parameters of the Naïve Bayesian Network for Essentiality / 5.3.3.3: |
Fully Connected Experimental Network / 5.3.3.4: |
Protein Interaction Networks / 5.4: |
Protein Interaction Network of Saccharomyces cerevisiae / 5.4.1: |
Protein Interaction Network of Escherichia coli / 5.4.2: |
Protein Interaction Network of Human / 5.4.3: |
Protein Domain Networks / 5.5: |
Bayesian Analysis of (Fake) Protein Complexes / 5.6: |
Protein-Protein Interaction Networks - Structural Hierarchies / 6: |
Protein Interaction Graph Networks / 6.1: |
Degree Distribution / 6.1.1: |
Clustering Coefficient / 6.1.2: |
Finding Cliques / 6.2: |
Random Graphs / 6.3: |
Scale-Free Graphs / 6.4: |
Detecting Communities in Networks / 6.5: |
Divisive Algorithms for Mapping onto Tree / 6.5.1: |
Modular Decomposition / 6.6: |
Modular Decomposition of Graphs / 6.6.1: |
Identification of Protein Complexes / 6.7: |
MCODE / 6.7.1: |
ClusterONE / 6.7.2: |
DACO / 6.7.3: |
Analysis of Target Gene Coexpression / 6.7.4: |
Network Growth Mechanisms / 6.8: |
Protein-DNA Interactions / 6.9: |
Transcription Factors / 7.1: |
Transcription Factor-Binding Sites / 7.2: |
Experimental Detection of TFBS / 7.3: |
Electrophoretic Mobility Shift Assay / 7.3.1: |
DNAse Footprinting / 7.3.2: |
Protein-Binding Micro arrays / 7.3.3: |
Chromatin Immunoprecipitation Assays / 7.3.4: |
Position-Specific Scoring Matrices / 7.4: |
Binding Free Energy Models / 7.5: |
Cis-Regulatory Motifs / 7.6: |
DACO Algorithm / 7.6.1: |
Relating Gene Expression to Binding of Transcription Factors / 7.7: |
Gene Expression and Protein Synthesis / 7.8: |
Regulation of Gene Transcription at Promoters / 8.1: |
Experimental Analysis of Gene Expression / 8.2: |
Real-time Polymerase Chain Reaction / 8.2.1: |
Microarray Analysis / 8.2.2: |
RNA-seq / 8.2.3: |
Statistics Primer / 8.3: |
t-Test / 8.3.1: |
z-Score / 8.3.2: |
Fisher's Exact Test / 8.3.3: |
Mann-Whitney-Wilcoxon Rank Sum Tests / 8.3.4: |
Kolmogorov-Smirnov Test / 8.3.5: |
Hypergeometric Test / 8.3.6: |
Multiple Testing Correction / 8.3.7: |
Preprocessing of Data / 8.4: |
Removal of Outlier Genes / 8.4.1: |
Quantile Normalization / 8.4.2: |
Log Transformation / 8.4.3: |
Differential Expression Analysis / 8.5: |
Volcano Plot / 8.5.1: |
SAM Analysis of Micro array Data / 8.5.2: |
Differential Expression Analysis of RNA-seq Data / 8.5.3: |
Negative Binomial Distribution / 8.5.3.1: |
DESeq / 8.5.3.2: |
Functional Enrichment / 8.6: |
Similarity of GO Terms / 8.7: |
Translation of Proteins / 8.8: |
Transcription and Translation Dynamics / 8.8.1: |
Gene Regulatory Networks / 8.9: |
Gene Regulatory Networks (GRNs) / 9.1: |
Gene Regulatory Network of E. coli / 9.1.1: |
Gene Regulatory Network of S. cerevisiae / 9.1.2: |
Graph Theoretical Models / 9.2: |
Coexpression Networks / 9.2.1: |
Bayesian Networks / 9.2.2: |
Dynamic Models / 9.3: |
Boolean Networks / 9.3.1: |
Reverse Engineering Boolean Networks / 9.3.2: |
Differential Equations Models / 9.3.3: |
DREAM: Dialogue on Reverse Engineering Assessment and Methods / 9.4: |
Input Function / 9.4.1: |
YAYG Approach in DREAM3 Contest / 9.4.2: |
Regulatory Motifs / 9.5: |
Feed-forward Loop (FFL) / 9.5.1: |
SIM / 9.5.2: |
Densely Overlapping Region (DOR) / 9.5.3: |
Algorithms on Gene Regulatory Networks / 9.6: |
Key-pathway Miner Algorithm / 9.6.1: |
Identifying Sets of Dominating Nodes / 9.6.2: |
Minimum Dominating Set / 9.6.3: |
Minimum Connected Dominating Set / 9.6.4: |
Regulatory Noncoding RNA / 9.7: |
Introduction to RNAs / 10.1: |
Elements of RNA Interference: siRNAs and miRNAs / 10.2: |
miRNA Targets / 10.3: |
Predicting miRNA Targets / 10.4: |
Role of TFs and miRNAs in Gene-Regulatory Networks / 10.5: |
Constructing TF/miRNA Coregulatory Networks / 10.6: |
TFmiR Web Service / 10.6.1: |
Construction of Candidate TF-miRNA-Gene FFLs / 10.6.1.1: |
Case Study / 10.6.1.2: |
Computational Epigenetics / 10.7: |
Epigenetic Modifications / 11.1: |
DNA Methylation / 11.1.1: |
CpG Islands / 11.1.1.1: |
Histone Marks / 11.1.2: |
Chromatin-Regulating Enzymes / 11.1.3: |
Measuring DNA Methylation Levels and Histone Marks Experimentally / 11.1.4: |
Working with Epigenetic Data / 11.2: |
Processing of DNA Methylation Data / 11.2.1: |
Imputation of Missing Values / 11.2.1.1: |
Smoothing of DNA Methylation Data / 11.2.1.2: |
Differential Methylation Analysis / 11.2.2: |
Comethylation Analysis / 11.2.3: |
Working with Data on Histone Marks / 11.2.4: |
Chromatin States / 11.3: |
Measuring Chromatin States / 11.3.1: |
Connecting Epigenetic Marks and Gene Expression by Linear Models / 11.3.2: |
Markov Models and Hidden Markov Models / 11.3.3: |
Architecture of a Hidden Markov Model / 11.3.4: |
Elements of an HMM / 11.3.5: |
The Role of Epigenetics in Cellular Differentiation and Reprogramming / 11.4: |
Short History of Stem Cell Research / 11.4.1: |
Developmental Gene Regulatory Networks / 11.4.2: |
The Role of Epigenetics in Cancer and Complex Diseases / 11.5: |
Metabolic Networks / 11.6: |
Introduction / 12.1: |
Resources on Metabolic Network Representations / 12.2: |
Stoichiometric Matrix / 12.3: |
Linear Algebra Primer / 12.4: |
Matrices: Definitions and Notations / 12.4.1: |
Adding, Subtracting, and Multiplying Matrices / 12.4.2: |
Linear Transformations, Ranks, and Transpose / 12.4.3: |
Square Matrices and Matrix Inversion / 12.4.4: |
Eigenvalues of Matrices / 12.4.5: |
Systems of Linear Equations / 12.4.6: |
Flux Balance Analysis / 12.5: |
Gene Knockouts: MOMA Algorithm / 12.5.1: |
OptKnock Algorithm / 12.5.2: |
Double Description Method / 12.6: |
Extreme Pathways and Elementary Modes / 12.7: |
Steps of the Extreme Pathway Algorithm / 12.7.1: |
Analysis of Extreme Pathways / 12.7.2: |
Elementary Flux Modes / 12.7.3: |
Pruning Metabolic Networks: NetworkReducer / 12.7.4: |
Minimal Cut Sets / 12.8: |
Applications of Minimal Cut Sets / 12.8.1: |
High-Flux Backbone / 12.9: |
Static Network Properties: Pathways / 12.10: |
Kinetic Modeling of cellular processes / 13: |
Biological Oscillators / 13.1: |
Circadian Clocks / 13.2: |
Role of Post-transcriptional Modifications / 13.2.1: |
Ordinary Differential Equation Models / 13.3: |
Examples for ODEs / 13.3.1: |
Modeling Cellular Feedback Loops by ODEs / 13.4: |
Protein Synthesis and Degradation: Linear Response / 13.4.1: |
Phosphorylation/Dephosphorylation - Hyperbolic Response / 13.4.2: |
Phosphorylation/Dephosphorylation - Buzzer / 13.4.3: |
Perfect Adaptation - Sniffer / 13.4.4: |
Positive Feedback - One-Way Switch / 13.4.5: |
Mutual Inhibition - Toggle Switch / 13.4.6: |
Negative Feedback - Homeostasis / 13.4.7: |
Negative Feedback: Oscillatory Response / 13.4.8: |
Cell Cycle Control System / 13.4.9: |
Partial Differential Equations / 13.5: |
Spatial Gradients of Signaling Activities / 13.5.1: |
Reaction-Diffusion Systems / 13.5.2: |
Dynamic Phosphorylation of Proteins / 13.6: |
Stochastic Processes in Biological Cells / 13.7: |
Stochastic Processes / 14.1: |
Binomial Distribution / 14.1.1: |
Poisson Process / 14.1.2: |
Master Equation / 14.1.3: |
Dynamic Monte Carlo (Gillespie Algorithm) / 14.2: |
Basic Outline of the Gillespie Method / 14.2.1: |
Stochastic Effects in Gene Transcription / 14.3: |
Expression of a Single Gene / 14.3.1: |
Toggle Switch / 14.3.2: |
Stochastic Modeling of a Small Molecular Network / 14.4: |
Model System: Bacterial Photosynthesis / 14.4.1: |
Pools-and-Proteins Model / 14.4.2: |
Evaluating the Binding and Unbinding Kinetics / 14.4.3: |
Pools of the Chromatophore Vesicle / 14.4.4: |
Steady-State Regimes of the Vesicle / 14.4.5: |
Parameter Optimization with Genetic Algorithm / 14.5: |
Protein-Protein Association / 14.6: |
Brownian Dynamics Simulations / 14.7: |
Dynamic Simulations of Networks / 14.8: |
Integrated Cellular Networks / 15: |
Response of Gene Regulatory Network to Outside Stimuli / 15.1: |
Whole-Cell Model of Mycoplasma genitalium / 15.2: |
Architecture of the Nuclear Pore Complex / 15.3: |
Integrative Differential Gene Regulatory Network for Breast Cancer Identified Putative Cancer Driver Genes / 15.4: |
Particle Simulations / 15.5: |
Outlook / 15.6: |
Index |