Computational Systems Biology, 2nd Edition

  • Published By:
  • ISBN-10: 0124059384
  • ISBN-13: 9780124059382
  • DDC: 570.1
  • Grade Level Range: College Freshman - College Senior
  • 548 Pages | eBook
  • Original Copyright 2013 | Published/Released June 2014
  • This publication's content originally published in print form: 2013

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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.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.

Table of Contents

Front Cover.
Half Title Page.
Title Page.
Copyright Page.
1: Introducing Computational Systems Biology.
2: Structural Systems Biology: Modeling Interactions and Networks for Systems Studies.
3: Understanding Principles of the Dynamic Biochemical Networks of Life through Systems Biology.
4: Biological Foundations of Signal Transduction, Systems Biology and Aberrations in Disease.
5: Complexities in Quantitative Systems Analysis of Signaling Networks.
6: Gene Networks: Estimation, Modeling, and Simulation.
7: Reconstruction of Metabolic Network from Genome Information and Its Structural and Functional Analysis.
8: Standards, Platforms, and Applications.
9: Databases, Standards, and Modeling Platforms for Systems Biology.
10: Computational Models for Circadian Rhythms: Deterministic versus Stochastic Approaches.
11: Top-Down Dynamical Modeling of Molecular Regulatory Networks.
12: Discrete Gene Network Models for Understanding Multicellularity and Cell Reprogramming: From Network Structure to Attractor Landscapes Landscape.
13: Stochastic Simulations of Cellular Processes: From Single Cells to Colonies.
14: Advances in Machine Learning for Processing and Comparison of Metagenomic Data.
15: Systems Biology of Infectious Diseases and Vaccines.
16: Computational Modeling and Simulation of Animal Early Embryogenesis with the Mecagen Platform.
17: Developing a Systems Biology of Aging.
18: Molecular Correlates of Morphometric Subtypes in Glioblastoma Multiforme.
19: Applications in Cancer Research: Mathematical Models of Apoptosis.
Author Index.
Subject Index.