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Computer Methods, Part C, Volume 487 [Hardback]

Volume editor (The Salk Institute, La Jolla, CA, USA)
  • Formāts: Hardback, 696 pages, height x width: 229x152 mm, weight: 1210 g
  • Sērija : Methods in Enzymology
  • Izdošanas datums: 22-Feb-2011
  • Izdevniecība: Academic Press Inc
  • ISBN-10: 0123812704
  • ISBN-13: 9780123812704
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Computer Methods, Part C, Volume 487Palielināt
  • Formāts: Hardback, 696 pages, height x width: 229x152 mm, weight: 1210 g
  • Sērija : Methods in Enzymology
  • Izdošanas datums: 22-Feb-2011
  • Izdevniecība: Academic Press Inc
  • ISBN-10: 0123812704
  • ISBN-13: 9780123812704
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9780123812704.html
Keywords:

The combination of faster, more advanced computers and more quantitatively oriented biomedical researchers has recently yielded new and more precise methods for the analysis of biomedical data. These better analyses have enhanced the conclusions that can be drawn from biomedical data, and they have changed the way that experiments are designed and performed. This volume, along with previous and forthcoming Computer Methods volumes for the Methods in Enzymology serial, aims to inform biomedical researchers about recent applications of modern data analysis and simulation methods as applied to biomedical research.

* Presents step-by-step computer methods and discusses the techniques in detail to enable their implementation in solving a wide range of problems * Informs biomedical researchers of the modern data analysis methods that have developed alongside computer hardware *Presents methods at the "nuts and bolts" level to identify and resolve a problem and analyze what the results mean



The combination of faster, more advanced computers and more quantitatively oriented biomedical researchers has recently yielded new and more precise methods for the analysis of biomedical data. These better analyses have enhanced the conclusions that can be drawn from biomedical data, and they have changed the way that experiments are designed and performed. This volume, along with the 2 previous Computer Methods volumes for the Methods in Enzymology serial, aims to inform biomedical researchers about recent applications of modern data analysis and simulation methods as applied to biomedical research.

* Presents step-by-step computer methods and discusses the techniques in detail to enable their implementation in solving a wide range of problems * Informs biomedical researchers of the modern data analysis methods that have developed alongside computer hardware *Presents methods at the "nuts and bolts" level to identify and resolve a problem and analyze what the results mean

Papildus informācija

Up-to-date methods aiming to inform biomedical researchers about recent applications of modern data analysis and simulation methods as applied to biomedical research
Contributors xiii
Preface xxi
Volumes in Series xxiii
1 Predicting Fluorescence Lifetimes and Spectra of Biopolymers
1(38)
Patrik R. Callis
1 Introduction
2(5)
2 Qualitative Concepts: Developing Intuition
7(7)
3 Methods
14(11)
4 Nonexponential Fluorescence Decay
25(3)
5 Final Remarks
28(6)
Acknowledgments
34(1)
References
34(5)
2 Modeling of Regulatory Networks: Theory and Applications in the study of the Drosophila Circadian Clock
39(34)
Elizabeth Y. Scribner
Hassan M. Fathallah-Shaykh
1 Introduction
40(2)
2 Developmental History of the Drosophila Circadian Clock
42(9)
3 Comparative Analysis of Three Network Regulatory Models
51(12)
4 The CWO Anomaly and a New Network Regulatory Rule
63(4)
5 Concluding Remarks
67(2)
References
69(4)
3 Strategies for Articulated Multibody-Based Adaptive Coarse Grain Simulation of RNA
73(26)
Mohammad Poursina
Kishor D. Bhalerao
Samuel C. Flores
Kurt S. Anderson
Alain Laederach
1 Introduction
74(4)
2 Need for the Development of Adaptive Coarse-Graining Machinery
78(5)
3 Metrics to Guide Transitions in Adaptive Modeling
83(6)
4 Adaptive Modeling Framework in DCA Scheme
89(7)
5 Conclusions
96(1)
Acknowledgments
96(1)
References
96(3)
4 Modeling Loop Entropy
99(34)
Gregory S. Chirikjian
1 Introduction
100(13)
2 Computing Bounds on the Entropy of the Unfolded Ensemble
113(6)
3 Approximating Entropy of the Loops in the Folded Ensemble
119(1)
4 Examples
120(7)
5 Conclusions
127(1)
Acknowledgments
128(1)
References
128(5)
5 Inferring Functional Relationships and Causal Network Structure from Gene Expression Profiles
133(14)
Radhakrishnan Nagarajan
Meenakshi Upreti
1 Introduction
134(2)
2 Methods
136(5)
3 Results
141(3)
4 Conclusions
144(1)
References
145(2)
6 Numerical Solution of the Chemical Master Equation: Uniqueness and Stability of the Stationary Distribution for Chemical Networks, and mRNA Bursting in a Gene Network with Negative Feedback Regulation
147(24)
E. S. Zeron
M. Santillan
1 Introduction
148(2)
2 The Chemical Master Equation
150(2)
3 Irreducible Chemical Reaction Systems
152(1)
4 Stability of the Chemical Master Equation Stationary Probability Distribution
153(4)
5 Two Different Algorithms to Calculate Stationary Probability Distributions for the Chemical Master Equation
157(3)
6 Gene Expression with Negative Feedback Regulation
160(7)
7 Concluding Remarks
167(1)
References
167(4)
7 How Molecular Should Your Molecular Model Be?
171(46)
Didier Gonze
Wassim Abou-Jaoude
Djomangan Adama Ouattara
Jose Halloy
1 Introduction
172(3)
2 Michaelis-Menten Kinetics Revisited
175(10)
3 Use of the Hill Kinetics for Transcription Rate
185(5)
4 Repressilator
190(8)
5 Toggle Switch
198(6)
6 Discussion
204(6)
7 Conclusion
210(1)
Acknowledgments
211(1)
References
211(6)
8 Computational Modeling of Biological Pathways by Executable Biology
217(36)
Maria Luisa Guerriero
John K. Heath
1 Introduction
218(2)
2 Executable Modeling Languages for Biology
220(6)
3 Intuitive Representation of Formal Models
226(7)
4 Case Studies
233(15)
5 Conclusions and Perspectives
248(1)
Acknowledgments
248(1)
References
248(5)
9 Computing Molecular Fluctuations in Biochemical Reaction Systems Based on a Mechanistic, Statistical Theory of Irreversible Processes
253(26)
Don Kulasiri
1 Introduction
254(2)
2 Theoretical Developments
256(4)
3 Elementary Chemical Reactions
260(2)
4 An Example of Chemical Reaction
262(4)
5 Activation of Transcriptional Factors
266(3)
6 Binding and Unbinding TF to E-boxes
269(4)
7 Binding and Unbinding of Activated TF to E-Boxes
273(4)
8 Conclusions
277(1)
Acknowledgments
277(1)
References
277(2)
10 Probing the Input-Output Behavior of Biochemical and Genetic Systems: System Identification Methods from Control Theory
279(40)
Jordan Ang
Brian Ingalls
David McMillen
1 Introduction
280(2)
2 System Identification Applied to a G-Protein Pathway
282(9)
3 System Identification
291(20)
4 Conclusion
311(5)
References
316(3)
11 Biochemical Pathway Modeling Tools for Drug Target Detection in Cancer and Other Complex Diseases
319(52)
Alberto Marin-Sanguino
Shailendra K. Gupta
Eberhard O. Voit
Julio Vera
1 Introduction and Overview
320(5)
2 Biomedical Knowledge and Data Retrieval: Constructing a Conceptual Map of a Biochemical Network
325(2)
3 Mathematical Modeling of Biochemical Networks: Translating Knowledge into Mathematical Equations
327(10)
4 Model Calibration: Matching the Mathematical Model to Quantitative Experimental Data
337(4)
5 Predictive Model Simulations as a Tool for Drug Discovery
341(4)
6 Model Sensitivity Analysis as a Tool for Detecting Critical Processes in Biochemical Networks
345(5)
7 Drug Target Detection Through Model Optimization
350(6)
8 One Step Further: Combining Mathematical Modeling with Drug Screening via Protein Docking-Based Techniques
356(3)
9 Final Remarks
359(8)
Acknowledgments
367(1)
References
367(4)
12 Deterministic and Stochastic Simulation and Analysis of Biochemical Reaction Networks: The Lactose Operon Example
371(26)
Necmettin Yildirim
Caner Kazanci
1 Introduction
372(1)
2 Mathematical Modeling of Biochemical Reaction Networks and Law of Mass Action
372(9)
3 Stochastic Simulations
381(5)
4 An Example: Lactose Operon in E. coli
386(7)
5 Conclusions and Discussion
393(2)
Acknowledgment
395(1)
References
395(2)
13 Multivariate Neighborhood Sample Entropy: A Method for Data Reduction and Prediction of Complex Data
397(12)
Joshua S. Richman
1 Introduction
398(1)
2 Current Methods and Limitations
398(1)
3 k-Nearest Neighbors
399(1)
4 Sample Entropy
400(1)
5 Multivariate Neighborhood Sample Entropy:Mn-SampEm
401(1)
6 Relationship Between kNN and MN-SampEn
402(1)
7 Relationship Between SampEn and MN-SampEn
402(1)
8 Applying MN-SampEn to Proteomics Data
403(1)
9 Algorithmic Implementation and Optimizing Tolerances
403(2)
10 Results
405(2)
11 Discussion
407(1)
12 Limitations and Future Directions
408(1)
References
408(1)
14 Scaling Differences of Heartbeat Excursions Between Wake and Sleep Periods
409(22)
L. Guzman-Vargas
I. Reyes-Ramirez
R. Hernandez-Perez
F. Angulo-Brown
1 Introduction
410(1)
2 Methods
411(3)
3 Data Analysis
414(13)
4 Conclusions
427(1)
Acknowledgments
428(1)
References
428(3)
15 Changepoint Analysis for Single-Molecule Polarized Total Internal Reflection Fluorescence Microscopy Experiments
431(34)
John F. Beausang
Yale E. Goldman
Philip C. Nelson
1 Overview
433(6)
2 Multiple Channels
439(3)
3 Detailed Analysis
442(8)
4 Simulation Results
450(7)
5 Discussion
457(4)
6 Conclusion
461(1)
Acknowledgments
462(1)
References
462(3)
16 Inferring Mechanisms from Dose-Response Curves
465(20)
Carson C. Chow
Karen M. Ong
Edward J. Dougherty
S. Stoney Simons Jr.
1 Introduction
466(1)
2 General Theory
467(5)
3 Application of Model to Data
472(7)
4 Discussion
479(3)
Acknowledgments
482(1)
References
482(3)
17 Spatial Aspects in Biological System Simulations
485(28)
Haluk Resat
Michelle N. Costa
Harish Shankaran
1 Introduction
486(3)
2 Methods and Frameworks
489(19)
3 Summary and Future Prospects
508(1)
Acknowledgments
509(1)
References
509(4)
18 Computational Approaches to Modeling Viral Structure and Assembly
513(32)
Stephen C. Harvey
Anton S. Petrov
Batsal Devkota
Mustafa Burak Boz
1 Introduction
514(1)
2 Double-Stranded DNA (dsDNA) Bacteriophage
514(12)
3 Single-Stranded RNA Viruses
526(14)
Acknowledgments
540(1)
References
540(5)
19 Rosetta3: An Object-Oriented Software Suite for the Simulation and Design of Macromolecules
545(30)
Andrew Leaver-Fay
Michael Tyka
Steven M. Lewis
Oliver F. Lange
James Thompson
Ron Jacak
Kristian Kaufman
P. Douglas Renfrew
Colin A. Smith
Will Sheffler
Ian W. Davis
Seth Cooper
Adrien Treuille
Daniel J. Mandell
Florian Richter
Yin-En Andrew Ban
Sarel J. Fleishman
Jacob E. Corn
David E. Kim
Sergey Lyskov
Monica Berrondo
Stuart Mentzer
Zoran Popovic
James J. Havranek
John Karanicolas
Rhiju Das
Jens Meiler
Tanja Kortemme
Jeffrey J. Gray
Brian Kuhlman
David Baker
Philip Bradley
1 Introduction
546(2)
2 Requirements
548(2)
3 Design Decisions
550(4)
4 Architecture
554(17)
5 Conclusion
571(1)
Acknowledgments
572(1)
References
572(3)
20 Computational Design of Intermolecular Stability and Specificity in Protein Self-assembly
575(20)
Vikas Nanda
Sohail Zahid
Fei Xu
Daniel Levine
1 Introduction
576(1)
2 Similarities and Differences Between Unimolecular Folding and Self-assembly
577(2)
3 Computational Approaches to Optimizing Stability and Specificity
579(5)
4 Collagen Self-assembly
584(3)
5 Considerations in Computational Design of Collagen Heteromers
587(4)
6 Conclusions
591(1)
References
591(4)
21 Differential Analysis of 2D Gel Images
595(16)
Feng Li
Francoise Seillier-Moiseiwitsch
1 Introduction
596(1)
2 Differential Analysis of 2D Gel Images
597(2)
3 Analyzing 2D Gel Images Using RegStatGel
599(7)
4 Illustration of an Exploratory Analysis Using RegStatGel
606(2)
5 Concluding Remarks
608(1)
References
609(2)
Author Index 611(16)
Subject Index 627