Advances in systems biology
Andrew B. Goryachev
Gespeichert in:
| Weitere Verfasser: | , |
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| Dokumenttyp: | Book/Monograph |
| Sprache: | Englisch |
| Veröffentlicht: |
New York, NY
Springer Science+Business Media, LLC
2012
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| Ausgabe: | 1 |
| Schriftenreihe: | Advances in experimental medicine and biology
736 |
| In: |
Advances in experimental medicine and biology (736)
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| Volumes / Articles: | Show Volumes / Articles. |
| DOI: | 10.1007/978-1-4419-7210-1 |
| Schlagworte: | |
| Online-Zugang: | Verlag, Volltext: https://doi.org/10.1007/978-1-4419-7210-1 Resolving-System, lizenzpflichtig, Volltext: http://dx.doi.org/10.1007/978-1-4419-7210-1 Cover: https://swbplus.bsz-bw.de/bsz359118771cov.jpg 
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| Verfasserangaben: | edited by Igor I. Goryanin, Andrew B. Goryachev |
Inhaltsangabe:
- Advances in Systems Biology; Preface; Contents; Contributors; Part I Multiscale Biological Networks: Identification, Modeling and Analysis; Chapter 1 Modular Analysis of Biological Networks; 1 Introduction; 2 Models of Biochemical Networks; 3 Graphs and Community Detection; 4 Stoichiometric Network Analysis and Metabolic Pathways; 5 Modules in Dynamic Networks: Definition by Behavior; 5.1 Local Structure: Network Motifs; 5.2 Global Decomposition: Monotone Systems; 5.3 Retroactivity; 5.4 Interfaces; 6 Applications: Modular Systems Identification and Analysis; 6.1 Control Systems
- 6.2 Modular Response Analysis7 Conclusions and Perspectives; References; Chapter 2 Modeling Signaling Networks Using High-throughput Phospho-proteomics; 1 Introduction; 2 Phospho-proteomics Data Collection; 2.1 Antibody-based Methods; 2.1.1 Intracellular Multicolor Flow Cytometry; 2.1.2 Microwestern Arrays; 2.1.3 Array and Bead-based Methods; 2.2 Mass Spectrometry; 2.2.1 Shotgun MS/MS; 2.2.2 Data Processing Challenges; 2.2.3 Quantitative MS; 2.2.4 MS for PTMs; 2.2.5 Limitations of the Shotgun MS/MS Approach; 2.2.6 Targeted MS/MS
- 3 Computational Analysis of Large Scale Phospho-proteomics Data Sets3.1 ``Descriptive" Approaches; 3.1.1 Global Investigations of the Phospho-proteome; 3.1.2 Analysis of Pathway Utilization Downstream of Receptors; 3.1.3 Analysis of Reciprocal Signaling in Cell-Cell Communication; 3.2 ``Predictive" Approaches; 3.2.1 Input/Output Regression Based Approaches; 3.2.2 Network Inference; 3.2.3 Bayesian Network Inference; 3.2.4 Reaction-based Models; 3.2.5 Rule-based Models; 3.2.6 Logic-based Models; 4 Summary; References
- Chapter 3 An Integrated Bayesian Framework for Identifying Phosphorylation Networks in Stimulated Cells1 Introduction; 2 Algorithm; 2.1 Calculating P(Mi|Kl Si); 2.2 Calculating P(li|KlSi); 2.3 Calculating P(Zlimax,limax|Kl Si); 2.4 The Log Likelihood Function; 2.5 Pseudo Code for the Above Algorithm; 3 Implementation of Our Algorithm to Analyze Phosphoproteomic Data; 3.1 Results; 4 Advantages and Disadvantages of Our Algorithm; 4.1 Advantages; 4.1.1 Inter Kinase Specificity; 4.1.2 Intra Kinase Specificity; 4.1.3 Feedback Interactions; 4.2 Disadvantages; 5 Conclusion; References
- Chapter 4 Signaling Cascades: Consequences of Varying Substrate and Phosphatase Levels1 Introduction; 2 One-Site Linear Signaling Cascades; 2.1 Steady States; 2.2 Concentrations at Steady State; 2.3 Splitting the Cascade; 3 Relationships Between Response Concentrations; 3.1 The Last Layer; 3.2 Intermediate Layers Response; 3.3 Total Amount of Kinase E; 4 Regulation Through Substrate and Phosphatase Variation; 5 Stimulus-Response Curves; 6 Maximal Response; 7 Discussion; References; Chapter 5 Heterogeneous Biological Network Visualization System: Case Study in Context of Medical Image Data
- 1 Introduction