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ECell System: Basic Concepts and Applications 2013 ed. [Kõva köide]

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  • Formaat: Hardback, 179 pages, kõrgus x laius: 254x178 mm, kaal: 558 g, XIV, 179 p., 1 Hardback
  • Sari: Molecular Biology Intelligence Unit 118
  • Ilmumisaeg: 25-Jan-2013
  • Kirjastus: Springer-Verlag New York Inc.
  • ISBN-10: 1461461561
  • ISBN-13: 9781461461562
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  • Formaat: Hardback, 179 pages, kõrgus x laius: 254x178 mm, kaal: 558 g, XIV, 179 p., 1 Hardback
  • Sari: Molecular Biology Intelligence Unit 118
  • Ilmumisaeg: 25-Jan-2013
  • Kirjastus: Springer-Verlag New York Inc.
  • ISBN-10: 1461461561
  • ISBN-13: 9781461461562
Teised raamatud teemal:

This book offers a comprehensive guide for E-Cell System version 3, showing how the E-Cell System, a multi-algorithm, multi-timescale object-oriented simulation platform, can be used to construct predictive virtual biological systems.



The interdisciplinary field of molecular systems biology aims to understand the behavior and mechanisms of biological processes composed of individual molecular components. As we gain more qualitative and quantitative information of complex intracellular processes, biochemical modeling and simulation become indispensable not only to uncover the molecular mechanisms of the processes, but to perform useful predictions. To this end, the E-Cell System, a multi-algorithm, multi-timescale object-oriented simulation platform, can be used to construct predictive virtual biological systems. Gene regulatory and biochemical networks that constitute a sub- or a whole cellular system can be constructed using the E-Cell System to perform qualitative and quantitative analyses. The purpose of E-Cell System: Basic Concepts and Applications is to provide a comprehensive guide for the E-Cell System version 3 in terms of the software features and its usage. While the publicly available E-Cell Simulation Environment version 3 User's Manual provides the technical details of model building and scripting, it does not describe some of the underlying concepts of the E-Cell System. The first part of the book addresses this issue by providing the basic concepts of modeling and simulation with the E-Cell System.
Part 1 Basic Concepts
1(62)
1 Introduction to Whole Cell Modeling
3(12)
Pawan K. Dhar
Modeling Fundamentals
3(10)
1 The Phenomenon
3(7)
2 Mathematical Representation
10(2)
3 Computer Simulation
12(1)
General Concepts on Whole Cell Modeling
13(2)
2 Foundations of E-Cell Simulation Environment Architecture
15(18)
Nathan Addy
Koichi Takahashi
Background
17(2)
The E-Cell System
19(2)
The Meta-Algorithm
21(2)
The E-Cell SE Kernel
23(6)
Interfaces to the Kernel
29(3)
Future Directions
32(1)
3 Distributed Cell Biology Simulations with the E-Cell System
33(10)
Masahiro Sugimoto
Design of ESM
34(4)
Parameter Estimation on ESM
38(1)
Discussion
39(4)
4 A Guide to Modeling Reaction-Diffusion of Molecules with the E-Cell System
43(20)
Satya Nanda Vel Arjunan
Spatiocyte Method
44(2)
Installing and Running Spatiocyte
46(3)
Spatiocyte Modules
49(14)
Part 2 Applications
63(114)
5 A Model Library of Bacterial Chemotaxis on E-Cell System
65(10)
Yuri Matsuzaki
Models and Methods
66(5)
Conclusion and Discussion
71(4)
6 Electrophysiological Simulation of Developmental Changes in Action Potentials of Cardiomyocytes
75(14)
Hitomi Itoh
Methods
79(4)
Results
83(3)
Discussion
86(3)
7 Simulation of Human Erythrocyte Metabolism
89(16)
Ayako Kinoshita
Simulation Analysis of Glucose-6-Phosphate Dehydrogenase (G6PDH) Deficiency
90(3)
Simulation Study for Methemoglobin Reduction Pathways
93(4)
Prediction by Mathematical Modeling and Its Verification by Metabolome Analysis for Oxygen Sensing Mechanism in Human Erythrocytes
97(8)
8 Dynamic Kinetic Modeling of Mitochondrial Energy Metabolism
105(38)
Katsuyuki Yugi
Construction of the Model
106(3)
Simulation Results
109(3)
Discussion
112(5)
Appendix A
117(22)
Rate Equations
139(4)
9 A Computational Model of the Hepatic Lobule
143(14)
Yasuhiro Naito
The Single Hepatocyte Model
144(1)
The Sinusoid Model
144(4)
Appendix: Details of the Mathematical Model
148(9)
10 Decoding the Signaling Mechanism of Toll-Like Receptor 4 Pathways in Wild Type and Knockouts
157(12)
Kumar Selvarajoo
Sankar Ghosh
Materials and Methods
158(2)
Results
160(1)
Discussion
161(5)
Appendix A
166(3)
11 Modeling of Hsp70-Mediated Protein Refolding
169(8)
Bin Hu
Matthias P. Mayer
Masaru Tomita
Materials and Methods
170(1)
Results
171(2)
Discussion and Conclusion
173(4)
Index 177
Satya Arjunan is a Postdoctoral Researcher at the RIKEN Quantitative Biology Center, Japan. He received his PhD in Systems Biology from Keio University (2009), BEng in Electronics Engineering (2000) and MSc (2003) in Computer Science from Universiti Teknologi Malaysia. He is also the recipient of the Texas Instruments Malaysia Scholarship (1997) and the Monbukagakusho Scholarship (2003). As part of his PhD work, he developed a multicompartmental spatiotemporal stochastic simulation method, called Spatiocyte, with applications in molecular systems biology.





Pawan K. Dhar is the Director of the Centre of Systems and Synthetic Biology, University of Kerala. Prior to this he held senior scientific positions at RIKEN Genomics Sciences Centre, Japan, Bioinformatics Institute, Singapore and the E-Cell group, Keio University in Japan and Manipal University. One of his key recent contributions has been to make functional proteins from noncoding genome. Dr. Dhar is the Founding Editor-in-Chief of the Springer's System and Synthetic Biology Journal. Dr. Dhar heads active research programs on synthetic proteins, virtual cell and BioCAD platform.









Masaru Tomita is a Professor and the Director General of the Institute for Advanced Biosciences, Keio University. He received PhD in Computer Science from Carnegie Mellon University (1985), PhD in Electrical Engineering from Kyoto University (1994) and PhD in Molecular Biology from Keio University (1998). He is a recipient of Presidential Young Investigators Award from National Science Foundation of USA (1988) and various other awards. His current research field includes Systems Biology, Metabolomics, and Computational Biology.