213 pages, 18 black & white illustrations, 35 colour illustrations
A fundamental problem in life sciences is the characterization of biological function. In medical sciences, understanding the bases of functional anomalies holds the key to effective diagnosis, treatment, and prognosis; in genetics, functional annotation of genetic variability uncovers the complex relationship between genotype and phenotype; in evolutionary biology, functional differences between diverse organisms highlight the evolutionary mechanisms that underlie the complexity of biological systems. With the successful completion of the human genome project and recent technological advances in biological data collection, it has become possible to study biological function from a systems perspective. Today, Systems Biology is established as a fundamental interdisciplinary science, which focuses on systematic study of the complex mechanisms that orchestrate the cooperation between diverse molecules that compose life.
In the study of biological systems, the complex interactions between biomolecules are often abstracted using network models. Molecular networks provide descriptions of the organization of various biological processes, including cellular signaling, metabolism, and genetic regulation. Knowledge on molecular networks provides the basis for systems level analysis of biological function. Research and method development for such analyses has grown tremendously in the past few years. This volume provides a detailed overview of existing knowledge on the functional characterization of biological networks. In eight chapters authored by an international group of systems biology and bioinformatics researchers, functional coherence of molecular networks is comprehensively explored from various perspectives, including network topology, modularity, functional inference, evolution, phenotype, disease, network dynamics, and molecular kinetics.
- Introduction to Network Biology
- Topological Characteristics of Molecular Networks
- Functional Annotation in Gene Networks
- Proteome Network Emulating Models
- Biological Network Alignment
- Pattern Mining across many Massive Biological Networks
- Molecular Networks and Complex Diseases
- Moving Towards Genome-Scale Kinetic Models: The Mass Action Stoichiometric Simulation Approach
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