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 vi
... Models for Circadian Rhythms: Deterministic versus Stochastic Approaches JEAN-CHRISTOPHE LELOUP, DIDIER GONZE, ALBERT GOLDBETER 1 Introduction: the computational biology of circadian rhythms 184 2 Modeling the Drosophila circadian clock ...
... Models for Circadian Rhythms: Deterministic versus Stochastic Approaches JEAN-CHRISTOPHE LELOUP, DIDIER GONZE, ALBERT GOLDBETER 1 Introduction: the computational biology of circadian rhythms 184 2 Modeling the Drosophila circadian clock ...
Seite 5
... models with the derived simulations. Chapter 10 builds on a classical mathematical modeling approach to study patterns of dynamic behaviors in biological systems. “Computational models for circadian rhythms - deterministic versus ...
... models with the derived simulations. Chapter 10 builds on a classical mathematical modeling approach to study patterns of dynamic behaviors in biological systems. “Computational models for circadian rhythms - deterministic versus ...
Seite 89
... circadian rhythms 104 4.3 Remarks 108 5 Conclusion 108 6 Related internet ... model for representing causal relationships among random variables by using ... model is suited for modeling qualitative relations between genes and allows ...
... circadian rhythms 104 4.3 Remarks 108 5 Conclusion 108 6 Related internet ... model for representing causal relationships among random variables by using ... model is suited for modeling qualitative relations between genes and allows ...
Seite 91
... modeling and simulation through an example of a gene network for mammalian circadian rhythms (Matsuno et al. 2005). 2. GENE. NETWORKESTIMATION. FROM. MICROARRAY. GENE. EXPRESSION. DATA. 2.1. Bayesian. networks. and. nonparametric.
... modeling and simulation through an example of a gene network for mammalian circadian rhythms (Matsuno et al. 2005). 2. GENE. NETWORKESTIMATION. FROM. MICROARRAY. GENE. EXPRESSION. DATA. 2.1. Bayesian. networks. and. nonparametric.
Seite 104
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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