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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Ergebnisse 1-5 von 27
Seite 24
... optimal for the organism if the extracellular conditions correspond to conditions that reigned during evolution. If we measure the changes in time of the extracellular 24 3. UNDERSTANDING PRINCIPLES OF THE DYNAMIC BIOCHEMICAL NETWORKS.
... optimal for the organism if the extracellular conditions correspond to conditions that reigned during evolution. If we measure the changes in time of the extracellular 24 3. UNDERSTANDING PRINCIPLES OF THE DYNAMIC BIOCHEMICAL NETWORKS.
Seite 25
... optimal efficiency has been shown not to apply completely in a number of cases. Organisms such as baker's yeast for instance do not grow at maximal efficiency when glucose is present in excess (Simeonidis et al. 2010). More in general ...
... optimal efficiency has been shown not to apply completely in a number of cases. Organisms such as baker's yeast for instance do not grow at maximal efficiency when glucose is present in excess (Simeonidis et al. 2010). More in general ...
Seite 26
... optimal, the task is: (3.5) maximize Z = fT·v subject to N·v = 0; vL ≤ v ≤ vU where vL and vU are the lower and upper bound of the fluxes (defining the range of values that the different rates can have), and f is a set of coefficients ...
... optimal, the task is: (3.5) maximize Z = fT·v subject to N·v = 0; vL ≤ v ≤ vU where vL and vU are the lower and upper bound of the fluxes (defining the range of values that the different rates can have), and f is a set of coefficients ...
Seite 27
... optimal pattern of internal fluxes representing the metabolic functioning of the cells cultured under specific conditions. This enables us to attempt to predict and compare the flux patterns of a control culture and a culture expressing ...
... optimal pattern of internal fluxes representing the metabolic functioning of the cells cultured under specific conditions. This enables us to attempt to predict and compare the flux patterns of a control culture and a culture expressing ...
Seite 30
... optimal with respect to a certain criterion or set of criteria. Extension of FBA to find alternate optimal solutions (Lee et al. 2000) or alternate optimal patterns of fluxes (Murabito et al. 2009) have been developed. In particular, an ...
... optimal with respect to a certain criterion or set of criteria. Extension of FBA to find alternate optimal solutions (Lee et al. 2000) or alternate optimal patterns of fluxes (Murabito et al. 2009) have been developed. In particular, an ...
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