Essential Numerical Computer Methods Reliable Lab Solutions 1st Edition by Michael L Johnson ISBN 0123849977 9780123849984

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ISBN 10: 0123849977 
ISBN 13: 9780123849984
Author: Michael L Johnson

The use of computers and computational methods has become ubiquitous in biological and biomedical research. During the last 2 decades most basic algorithms have not changed, but what has is the huge increase in computer speed and ease of use, along with the corresponding orders of magnitude decrease in cost.

A general perception exists that the only applications of computers and computer methods in biological and biomedical research are either basic statistical analysis or the searching of DNA sequence data bases. While these are important applications they only scratch the surface of the current and potential applications of computers and computer methods in biomedical research. The various chapters within this volume include a wide variety of applications that extend far beyond this limited perception. As part of the Reliable Lab Solutions series, Essential Numerical Computer Methods brings together chapters from volumes 210, 240, 321, 383, 384, 454, and 467 of Methods in Enzymology. These chapters provide a general progression from basic numerical methods to more specific biochemical and biomedical applications.

Essential Numerical Computer Methods Reliable Lab Solutions 1st Table of contents:

1. Chapter 1: Use of Least-Squares Techniques in Biochemistry
2. Chapter 2: Parameter Estimates from Nonlinear Models
3. Chapter 3: Analysis of Residuals: Criteria for Determining Goodness-of-Fit
4. Chapter 4: Monte Carlo Method for Determining Complete Confidence Probability Distributions of Estimated Model Parameters
5. Chapter 5: Effects of Heteroscedasticity and Skewness on Prediction in Regression: Modeling Growth of the Human Heart
6. Chapter 6: Singular Value Decomposition: Application to Analysis of Experimental Data
7. Chapter 7: Irregularity and Asynchrony in Biologic Network Signals
8. Chapter 8: Distinguishing Models of Growth with Approximate Entropy
9. Chapter 9: Application of the Kalman Filter to Computational Problems in Statistics
10. Chapter 10: Bayesian Hierarchical Models
11. Chapter 11: Mixed-Model Regression Analysis and Dealing with Interindividual Differences
12. Chapter 12: Distribution Functions from Moments and the Maximum-Entropy Method
13. Chapter 13: The Mathematics of Biological Oscillators
14. Chapter 14: Modeling of Oscillations in Endocrine Networks with Feedback
15. Chapter 15: Boundary Analysis in Sedimentation Velocity Experiments
16. Chapter 16: Statistical Error in Isothermal Titration Calorimetry
17. Chapter 17: Physiological Modeling with Virtual Cell Framework
18. Chapter 18: Fractal Applications in Biology: Scaling Time in Biochemical Networks
19. Chapter 19: Analytical Methods for the Retrieval and Interpretation of Continuous Glucose Monitoring Data in Diabetes
20. Chapter 20: Analyses for Physiological and Behavioral Rhythmicity
21. Chapter 21: Evaluation and Comparison of Computational Models
22. Chapter 22: Algebraic Models of Biochemical Networks
23. Chapter 23: Monte Carlo Simulation in Establishing Analytical Quality Requirements for Clinical Laboratory Tests: Meeting Clinical Needs
24. Chapter 24: Pancreatic Network Control of Glucagon Secretion and Counterregulation

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