Cover image for Handbook of statistical genetics
Title:
Handbook of statistical genetics
Edition:
2nd ed.
Publication Information:
West Sussex : John Wiley & Sons, 2003
ISBN:
9780470848296

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30000010047192 QH438.4.S73 H36 2003 v.1 Reference Book Handbook
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30000010047193 QH438.4.S73 H36 2003 v.2 Reference Book Handbook
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Summary

Summary

From the Reviews of the First Edition:
"This magnificent book attempts to catalogue and introduce all aspects of modern statistical genetics...I can thoroughly recommend it."
Short Book Reviews of ISI
"...extremely well written and referenced work, which must come highly recommended..."
Statistical Methods in Medical Research Provides comprehensive coverage of a thriving area of research Features nine newly commissioned chapters All existing chapters have been fully updated with new advances in the field and new references Now includes a glossary of terms, and a list of acronyms and abbreviations. Features extensive cross-referencing between chapters. Each chapter is written by a leading international authority from the field. Complemented by examples, case studies, and references to useful resources on the web.


Table of Contents

Volume 1 List of Contributors
Editor's Preface to the Third Edition
Glossary of Terms
Abbreviations and Acronyms
Part 1 Genomes
1 Chromosome MapsT.P. Speed and H. Zhao
1.1 Introduction
1.2 Genetic Maps
1.3 Physical Maps
1.4 Radiation Hybrid Mapping
1.5 Other Physical Mapping Approaches
1.6 Gene Maps
Acknowledgments
References
2 Statistical Significance in Biological Sequence ComparisonW.R. Pearson and T.C. Wood
2.1 Introduction
2.2 Statistical Significance and Biological Significance
2.3 Estimating Statistical Significance for Local Similarity Searches
2.4 Summary: Exploiting Statistical Estimates
Acknowledgments
References
3 Bayesian Methods in Biological Sequence AnalysisJun S. Liu and T. Logvinenko
3.1 Introduction
3.2 Overview of the Bayesian Methodology
3.3 Hidden Markov Model: A General Introduction
3.4 Pairwise Alignment of Biological Sequences
3.5 Multiple Sequence Alignment
3.6 Finding Recurring Patterns in Biological Sequences
3.7 Joint Analysis of Sequence Motifs and Expression Microarrays
3.8 Summary
Acknowledgments
Appendix A Markov Chain Monte Carlo Methods
References
4 Statistical Approaches in Eukaryotic Gene PredictionV. Solovyev
4.1 Structural Organization and Expression of Eukaryotic Genes
4.2 Methods of Functional Signal Recognition
4.3 Linear Discriminant Analysis
4.4 Prediction of Donor and Acceptor Splice Junctions
4.5 Identification of Promoter Regions in Human DNA
4.6 Recognition of PolyA Sites
4.7 Characteristics for Recognition of 3-Processing Sites
4.8 Identification of Multiple Genes in Genomic Sequences
4.9 Discriminative and Probabilistic Approaches for Multiple Gene Prediction
4.10 Internal Exon Recognition
4.11 Recognition of Flanking Exons
4.12 Performance of Gene Identification Programs
4.13 Using Protein Similarity Information to Improve Gene Prediction
4.14 Genome Annotation Assessment Project (EGASP)
4.15 Annotation of Sequences from Genome Sequencing Projects
4.16 Characteristics and Computational Identification of miRNA genes
4.17 Prediction of microRNA Targets
4.18 Internet Resources for Gene Finding and Functional Site Prediction
Acknowledgments
References
5 Comparative GenomicsJ. Dicks and G. Savva
5.1 Introduction
5.2 Homology
5.3 Genomic Mutation
5.4 Comparative Maps
5.5 Gene Order and Content
5.6 Whole Genome Sequences
5.7 Conclusions and Future Research
Acknowledgments
References
Part 2 Beyond the Genome
6 Analysis of Microarray Gene Expression DataW. Huber and A. von Heydebreck and M. Vingron
6.1 Introduction
6.2 Data Visualization and Quality Control
6.3 Error Models, Calibration and Measures of Differential Expression
6.4 Identification of Differentially Expressed Genes
6.5 Pattern Discovery
6.6 Conclusions
Acknowledgments
References
7 Statistical Inference for Microarray StudiesS.B. Pounds and C. Cheng and A. Onar
7.1 Introduction
7.2 Initial Data Processing
7.3 Testing the Association of Phenotype with Expression
7.4 Multiple Testing
7.5 Annotation Analysis
7.6 Validation Analysis
7.7 Study Design and Sample Size
7.8 Discussion Related Chapters
References
8 Bayesian Methods for Microarray DataA. Lewin and S. Richardson
8.1 Introduction
8.2 Extracting Signal From Observed Intensi