- Logical information flow aids understanding of basic building blocks of life through disease phenotypes
- Evolved principles gives insight into underlying organizational principles of biological organizations, and systems processes, governing functions such as adaptation or response patterns
- Coverage of technical tools and systems helps researchers to understand and resolve specific systems biology problems using advanced computation
- Multi-scale modeling on disparate scales aids researchers understanding of dependencies and constraints of spatio-temporal relationships fundamental to biological organization and function.
This comprehensively revised second edition of Computational Systems Biology discusses the experimental and theoretical foundations of the function of biological systems at the molecular, cellular or organismal level over temporal and spatial scales, as systems biology advances to provide clinical solutions to complex medical problems. In particular the work focuses on the engineering of biological systems and network modeling.
Graduate students and researchers in Bioinformatics, Biocomputing, Theoretical Biology, Biochemistry/Biophysics, and Cell Biology.
Computational Systems Biology, 2nd Edition
Introducing Computational Systems Biology; Protein Interactions, Stability and Regulation; Transcriptional control; Introduction to Computational Models of Biochemical Reaction Networks; Biological Foundations of Signal Transduction and Aberrations in Disease; A discrete approach to top-down modeling of biochemical networks; Reconstruction of metabolic network from genome information and its structural and functional analysis; Gene networks: estimation, modeling and simulation; Standards, platforms and tools; Computational models for circadian rhythms: Deterministic versus stochastic approaches; Integrated imaging informatics; Imaging and Modeling of complex tumor formation; Imaging to help decipher an model higher orders of complexity; Multistability and multicellularity: cell fates as high-dimensional attractors of gene regulatory networks; Whole Cell Modeling; Databases for Systems Biology; Systems Biology of the Microbiome; Systems Immunology; Applying systems biology to understand the immune response to infection and vaccination; Aging and Systems Biology; From Cardiac Mitochondria to Systems Physiology; Cancer Systems Biology; Systems Medicine, Drug Biology and Interventions; Towards a blueprint of an entire organism