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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Seite 22
... corresponds to the dilution due to growth at the specific growth rate μ. Doing this for all reactions and generalizing to vectors and matrix this leads to: (3.2) dX dt = N·v − μ·X Here v is a column of all the rates of all the ...
... corresponds to the dilution due to growth at the specific growth rate μ. Doing this for all reactions and generalizing to vectors and matrix this leads to: (3.2) dX dt = N·v − μ·X Here v is a column of all the rates of all the ...
Seite 23
... correspond to the solution of the biological question how an organism builds itself from components it takes from the environment, i.e. of how an organism recreates life from dead materials. For many components an organism cannot be ...
... correspond to the solution of the biological question how an organism builds itself from components it takes from the environment, i.e. of how an organism recreates life from dead materials. For many components an organism cannot be ...
Seite 24
... corresponding to steady state, which corresponds to a zero dimensional space. Evolution has selected the values of all the internal parameters such that a steady state can be obtained (see above) and possibly such that the actual rates ...
... corresponding to steady state, which corresponds to a zero dimensional space. Evolution has selected the values of all the internal parameters such that a steady state can be obtained (see above) and possibly such that the actual rates ...
Seite 26
From Molecular Mechanisms to Disease Andres Kriete, Roland Eils. correspond to substances that are not present in the ... corresponding reaction rates (elements of rate vector v) to be zero, one may again try to find a solution for the ...
From Molecular Mechanisms to Disease Andres Kriete, Roland Eils. correspond to substances that are not present in the ... corresponding reaction rates (elements of rate vector v) to be zero, one may again try to find a solution for the ...
Seite 28
... corresponding to the maximal yield shows the glucose uptake flux entirely entering the TCA cycle, with no lactate production. To retrieve a flux pattern highlighting the cancer metabolic features (a constitutive activation of the branch ...
... corresponding to the maximal yield shows the glucose uptake flux entirely entering the TCA cycle, with no lactate production. To retrieve a flux pattern highlighting the cancer metabolic features (a constitutive activation of the branch ...
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 |
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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