Computational Systems Biology: From Molecular Mechanisms to DiseaseAndres Kriete, Roland Eils Academic Press, 26.11.2013 - 548 Seiten 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.
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Im Buch
Ergebnisse 1-5 von 95
Seite xiii
... experimental validation of model predictions, whereby a formal reasoning becomes key. This requires a collaborative input of experimental and theoretical biologists working together with system analysts, computer scientists ...
... experimental validation of model predictions, whereby a formal reasoning becomes key. This requires a collaborative input of experimental and theoretical biologists working together with system analysts, computer scientists ...
Seite 2
... experiment is designed and performed. This process continues until sufficient experimental evidence in favor of the model is collected. Once the system has been identified and a model constructed, the system behavior can be studied, for ...
... experiment is designed and performed. This process continues until sufficient experimental evidence in favor of the model is collected. Once the system has been identified and a model constructed, the system behavior can be studied, for ...
Seite 4
... of how high-throughput experimental techniques can help to accelerate reconstruction and simulation of signaling pathways. This is the theme of the 4 1. INTROduCINg COmPuTATIONAl SySTEmS BIOlOgy 2 Overview of the content.
... of how high-throughput experimental techniques can help to accelerate reconstruction and simulation of signaling pathways. This is the theme of the 4 1. INTROduCINg COmPuTATIONAl SySTEmS BIOlOgy 2 Overview of the content.
Seite 5
... experimental data, elements of biological systems, and mathematical models with the derived simulations. Chapter 10 builds on a classical mathematical modeling approach to study patterns of dynamic behaviors in biological systems ...
... experimental data, elements of biological systems, and mathematical models with the derived simulations. Chapter 10 builds on a classical mathematical modeling approach to study patterns of dynamic behaviors in biological systems ...
Seite 7
... experimental, and methodical resources. Increase in data quality and coherence, availability within integrated databases or approaches that can manage experimental variability, are less considered but may be as essential for robust ...
... experimental, and methodical resources. Increase in data quality and coherence, availability within integrated databases or approaches that can manage experimental variability, are less considered but may be as essential for robust ...
Inhalt
1 | |
9 | |
21 | |
45 | |
65 | |
89 | |
7 Reconstruction of Metabolic Network from Genome Information and its Structural and Functional Analysis | 113 |
8 Standards Platforms and Applications | 133 |
From Network Structure to Attractor Landscapes Landscape | 241 |
From Single Cells to Colonies | 277 |
14 Advances in Machine Learning for Processing and Comparison of Metagenomic Data | 295 |
15 Systems Biology of Infectious Diseases and Vaccines | 331 |
16 Computational Modeling and Simulation of Animal Early Embryogenesis with the MecaGen Platform | 359 |
17 Developing a Systems Biology of Aging | 407 |
18 Molecular Correlates of Morphometric Subtypes in Glioblastoma Multiforme | 423 |
Mathematical Models of Apoptosis | 455 |
9 Databases Standards and Modeling Platforms for Systems Biology | 169 |
Deterministic versus Stochastic Approaches | 183 |
11 TopDown Dynamical Modeling of Molecular Regulatory Networks | 223 |
Author Index | 483 |
Subject Index | 525 |
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Computational Systems Biology: From Molecular Mechanisms to Disease Andres Kriete,Roland Eils Keine Leseprobe verfügbar - 2013 |
Häufige Begriffe und Wortgruppen
activation algorithm analysis annotation apoptosis approach attractor Bayesian networks behavior binding biochemical Bioinformatics Biol Boolean network cancer caspase caspase-8 cell types CellML cellular circadian clock circadian oscillations circadian rhythms coefficient complex concentration corresponding cycle database described deterministic differentiation discrete domain Drosophila dynamics embryo enzyme equations experimental feedback Figure flux gene expression gene networks gene regulatory networks genetic genome Goldbeter graph identify immune integration interactions intracellular k-mers KEGG kinase kinetic Leloup ligand mammalian mathematical models mechanisms membrane metabolic network metabolites metagenomic methods microarray model for circadian modules molecular molecules mRNA network model nodes optimal organisms parameter perturbation phosphorylation predict protein proteomics quantitative reactions receptor regulation represent response robustness samples SBML sequences signal transduction signaling networks signaling pathways simulation specific stochastic structure tion tissue transcription transition vaccine variables XIAP