Computational Systems Biology: From Molecular Mechanisms to DiseaseThis 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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Seite 31
We first discuss the example of a signal-transduction cascade with all proteins in
the inactive un-phosphorylated state, ... The rate of phosphorylation of the target
of this receptor (which we here assume to be a protein kinase) will jump from ...
We first discuss the example of a signal-transduction cascade with all proteins in
the inactive un-phosphorylated state, ... The rate of phosphorylation of the target
of this receptor (which we here assume to be a protein kinase) will jump from ...
Seite 50
The principal modes that are used for intracellular communication are:
phosphorylation, second messengers, degradation, and complex formation. 2.2.1
Phosphorylation In order to convey an intracellular signal, introduced
modifications have ...
The principal modes that are used for intracellular communication are:
phosphorylation, second messengers, degradation, and complex formation. 2.2.1
Phosphorylation In order to convey an intracellular signal, introduced
modifications have ...
Seite 51
The transition between the two states is highly regulated by phosphorylation,
interaction with additional domains and/ or binding of regulatory proteins. This
tight regulatory mechanism was first identified in cytoplasmic tyrosine protein
kinases ...
The transition between the two states is highly regulated by phosphorylation,
interaction with additional domains and/ or binding of regulatory proteins. This
tight regulatory mechanism was first identified in cytoplasmic tyrosine protein
kinases ...
Seite 187
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Inhalt
1 | |
9 | |
21 | |
45 | |
5 Complexities in Quantitative Systems Analysis of Signaling Networks | 65 |
Estimation Modeling and Simulation | 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