The new research area of genomics-inspired network biology lacks an introductory book that enables both physical/computational scientists and biologists to obtain a general yet sufficiently rigorous perspective of current thinking. Filling this gap, Introduction to Biological Networks provides a thorough introduction to genomics-inspired network biology for physical scientists and biologists involved in interdisciplinary research.
The book focuses on the concept of molecular and genetic interaction networks as a paradigm for interpreting the complexity of molecular biology at a genomic scale. The authors describe the experimental methods used to discover and test networks of interaction among biological molecules. They also present computational methods for predicting the interaction networks, discuss general mechanisms of network formation and evolution, and explore the application of network approaches to important problems in biology and medicine.
With many examples throughout and clear explanations of key concepts, this book is the first to offer a broad treatment of genomics-inspired network biology with sufficient mathematical and biological rigor. It gives readers a conceptual understanding of this burgeoning scientific field.
TOC:
Table of Contents
The Living Interactome
Biological Function Depends on Context
The Nature of Interactions
Network as a Metaphor in Biology
Metabolic Networks
Robustness at the Network Level
Experimental Inference of Interactions
Direct versus Indirect Inference of Interactions
Physical versus Genetic Interactions
The Two-Hybrid Interaction
Affinity Co-Purification
DNA-Protein Interactions
Classification and Interpretation of Genetic Interactions
Inference of Genetic Interactions
Prediction of Physical Interactions
Entropy and Information
Boolean Networks REVEAL Regulatory Interactions
Variants of the REVEAL Method
Dynamic Bayesian Networks
Predicting Protein-Protein Interactions
Data Integration to Improve Prediction Performance
Metabolic Networks and Genetic Interactions
Optimal Metabolic States and Flux Balance Analysis
Minimization of Metabolic Adjustment and Gene Deletions
Predicting Genetic Interactions among Metabolic Genes
General Methods for Predicting Genetic Interactions
Approaches for Integrated Prediction of Networks
Testing Inferred Networks
Co-Expression as a Test of Physical Interaction
An Experimental Test of Predicted Protein-Protein Interactions
Combining Protein Interactions Discovered by High-Throughput Experiments
From Curated Protein-Protein Interactions to Protein Complexes
Testing DNA-Protein Interactions
Congruence of Biological Function among Interacting Partners
Testing Genetic Interactions
Structure-Based Tests of Interaction
Small Model Networks
Life Cycle of the Lambda Phage
Interaction Network in the Lysis-Lysogeny Decision
Recruitment of Proteins as a Theme in Regulatory Networks
The Network of Cell Cycle Regulation
Tractable Models of Large Networks
Models of Regular Networks
Random Network Models
Evolving Networks by Preferential Attachment
Evolving Networks Based on Gene Duplication
Reconstruction of Ancient Networks from Modern Ones
Large-Scale Biophysics-Inspired Models for Protein Interaction Networks
Network Modularity and Robustness
Modularity Implies Robustness in the Drosophila Segment Polarity Network
Topological and Functional Aspects of Network Modularity
Robustness Implications of Topology of Biological Networks
Robustness and Network Dynamics
Network Robustness by Rewiring
Networks and Disease
Disease Loci Identification and Mapping
Network as a Paradigm for Linking Diseases and Disease Genes
Network-Based Prediction of Disease Genes
Network Analysis of Disease Mechanisms and Disease Response
Network-Based Prediction of Disease Comorbidity
Cancer and Synthetic Lethality