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Computational Methods for Genetics of Complex Traits

by: Moore; Dunlap

Computational Methods for Genetics of Complex Traits

by: Moore; Dunlap

ISBN 13:
9780123808622
ISBN 10:
0123808626
Format: Hardcover
Copyright: 11/02/2010
Publisher: Elsevier Science

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Summary

Genes interact with environment, experience, and the biology of the brain to shape an animal's behavior. This latest volume in Advances in Genetics, organized according to the most widely used model organisms, describes the latest genetic discoveries in relation to neural circuit development and activity. * Explores latest topics in neural circuits and behavior research in zebrafish, drosophila, c.elegans, and mouse models * Includes methods for testing with ethical, legal, and social implications * Critically analyzes prospects future prospects

Contributors	p. ix
Genome Simulation: Approaches for Synthesizing In Silico Datasets for Human Genomics	p. 1
Introduction	p. 2
Genome Simulation Challenges	p. 4
General Simulation Strategies	p. 5
A Forward-Time Simulation Example: genomeSIMLA	p. 8
GenomeSIMLA: An Experimental Example	p. 16
Conclusions	p. 20
References	p. 21
Logic Regression and its Extensions	p. 25
Introduction	p. 26
Logic Regression	p. 29
Modifications and Extensions of Logic Regression	p. 37
References	p. 43
Complex System Approaches to Genetic Analysis: Bayesian Approaches	p. 47
Introduction	p. 48
Structure of Covariates	p. 53
Estimation	p. 55
Model Uncertainty	p. 61
Determining Noteworthiness	p. 64
Conclusions	p. 66
References	p. 68
Multigenic Modeling of Complex Disease by Random Forests	p. 73
Introduction	p. 74
Random Forests	p. 76
Prediction	p. 81
Variable Selection	p. 83
Interpretation of the Results	p. 93
Conclusions	p. 96
References	p. 97
Detecting, Characterizing, and Interpreting Nonlinear Gene-Gene Interactions Using Multifactor Dimensionality Reduction	p. 101
Introduction	p. 102
Machine Learning Analysis of Gene-Gene Interactions Using MDR	p. 105
Filter Approaches to MDR	p. 107
Wrapper Approaches to MDR	p. 109
Statistical Interpretation of MDR Models	p. 110
Summary	p. 112
References	p. 113
The Restricted Partition Method	p. 117
Why Look for Joint Genetic Effects?	p. 118
Key Concerns Addressed by the RPM	p. 120
Description of the RPM	p. 127
Computational Issues	p. 133
Other Practical Issues	p. 135
Summary	p. 138
References	p. 138
Statistical Methods for Pathway Analysis of Genome-Wide Data for Association with Complex Genetic Traits	p. 141
Introduction	p. 142
What Is Pathway Analysis?	p. 143
Statistical Considerations When Analyzing GWAS Data	p. 144
Statistical Methods for Pathway Analysis	p. 145
Publically Available Pathway Databases	p. 158
Unresolved Analytical Issues and Scope for Further Research	p. 165
Software Packages for Pathway Analysis of GWAS Data	p. 172
Conclusions	p. 172
References	p. 174
Providing Context and Interpretability to Genetic Association Analysis Results Using the KGraph	p. 181
Introduction	p. 182
The Role of Correlation Structure in Interpreting Results	p. 183
Improving Interpretability by Including Context-Dependent Effects	p. 184
Overview of the KGraph's Structure	p. 184
Creating and Exploring KGraphs	p. 187
Exploring Genetic Architecture in Real-World Data Using a KGraph	p. 187
Enhancements and Future Directions for the KGraph	p. 191
Conclusion	p. 192
References	p. 192
Index	p. 195
Table of Contents provided by Ingram. All Rights Reserved.

Amazon no longer offers textbook rentals. We do!

Computational Methods for Genetics of Complex Traits

Computational Methods for Genetics of Complex Traits

9780123808622

0123808626

Summary

Table of Contents

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