Computational Systems Biology, 2nd Edition,Andres Kriete,Roland Eils,ISBN9780124059269
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Computational Systems Biology, 2nd Edition

From Molecular Mechanisms to Disease

Print Book

Editor(s) : Kriete  &   Eils  

Expected Release Date:

Imprint: Academic Press

ISBN: 9780124059269

Pages: 464

Dimensions: 229 X 152

A timely review of the central topics of systems biology, emphasizing computational tools and bioinformatics, and showcasing newer modeling, simulation and analysis techniques such as multi-scale modeling and analysis

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Key Features

  • Offers a logical information flow that aids understanding of basic building blocks of life through disease phenotypes
  • Gives insight into underlying organizational principles of biological organizations, and systems processes, governing functions such as adaptation or response patterns through evolved principles
  • Includes coverage of technical tools and systems helps researchers to understand and resolve specific systems biology problems using advanced computation
  • Features multi-scale modeling on disparate scales which aids researchers in understanding dependencies and constraints of spatio-temporoal relationships fundamental to biological organization and function.

Description

This comprehensively revised new edition of the classic work 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.

NEW TO THIS EDITION:
- New concepts and methods for abstracting, compiling, simulating and analyzing computational models.
- Information storage, mining and knowledge extraction
- Reverse engineering of gene and metabolomic networks
- New methods and computational aspects
- Modeling and simulation of multicellular systems in health and disease.
- Selected contributions include bottom-up strategies that predict emergent biological properties, top-down concepts that elucidate form and function, as well as advanced applications including clinical, translational systems biology.

Readership

Graduate students and researchers in Bioinformatics, Biocomputing, Theoretical Biology, Biochemistry/Biophysics, and Cell Biology.

Andres Kriete

Affiliations and Expertise

Drexel University, Philadelphia, PA and Coriell Institute for Medical Research, Camden, NJ, USA

Roland Eils

Affiliations and Expertise

Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, and Bioinformatics and Functional Genomics, Institute of Pharmacy and Molecular Biotechnology, University of Heidelberg, Germany

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

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Computational Systems Biology