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Contents Contributors Foreword Lon Cardon Preface Glossary SECTION I AN INTRODUCTION TO BIOINFORMATICS FOR THE GENETICIST 1 Bioinformatics challenges for the geneticist Michael R. Barnes 1.1 Introduction 1.2 The role of bioinformatics in genetics research 1.3 Genetics in the post-genome era 1.4 Conclusions References 2 Managing and manipulating genetic data Karl W. Broman and Simon C. Heath 2.1 Introduction 2.2 Basic principles 2.3 Data entry and storage 2.4 Data manipulation 2.5 Examples of code 2.6 Resources 2.7 Summary References SECTION II MASTERING GENES, GENOMES AND GENETIC VARIATION DATA 3 The HapMap ? A Haplotype map of the human genome Ellen M. Brown and Bryan J. Barratt 3.1 Introduction 3.2 Accessing the data 3.3 Application of HapMap data in association studies 3.4 Future perspectives References 4 Assembling a view of the human genome Colin A. M. Semple 4.1 Introduction 4.2 Genomic sequence assembly 4.3 Annotation from a distance: the generalities 4.4 Annotation up close and personal: the specifics 4.5 Annotation: the next generation References 5 Finding, delineating and analysing genes Christopher D. Southan and Michael R. Barnes 5.1 Introduction 5.2 Why learn to predict and analyse genes in the complete genome era? 5.3 The evidence cascade for gene products 5.4 Dealing with the complexities of gene models 5.5 Locating known genes in the human genome 5.6 Genome portal inspection 5.7 Analysing novel genes 5.8 Conclusions and prospects References 6 Comparative genomics Martin S. Taylor and Richard R. Copley 6.1 Introduction 6.2 The genomic landscape 6.3 Concepts 6.4 Practicalities 6.5 Technology 6.6 Applications 6.7 Challenges and future directions 6.8 Conclusion References SECTION III BIOINFORMATICS FOR GENETIC STUDY DESIGN AND ANALYSIS 7 Identifying mutations in single-gene disorders David P. Kelsell, Diana Blaydon and Charles A. Mein 7.1 Introduction 7.2 Clinical ascertainment 7.3 Genome-wide mapping of monogenic diseases 7.4 The nature of mutation in monogenic diseases 7.5 Considering epigenetic effects in Mendelian traits 7.6 Summary References 8 From genome scan to culprit gene: refining loci implicated by genome scans Ian C. Gray 8.1 Introduction 8.2 Theoretical and practical considerations 8.3 A stepwise approach to locus refinement and candidate gene identification 8.4 Conclusion 8.5 A list of the software tools and Web links mentioned in this chapter References 9 Integrating genetics, genomics and epigenomics to identify disease genes Michael R. Barnes 9.1 Introduction 9.2 Dealing with the (draft) human genome sequence 9.3 Progressing loci of interest with genomic information 9.4 In silico characterization of the IBD5 locus ? a case study 9.5 Drawing together biological rationale ? hypothesis building 9.6 Identification of potentially functional polymorphisms 9.7 Conclusions References 10 Tools for statistical analysis of genetic data Aruna Bansal, Charlotte Vignal and Ralph McGinnis 10.1 Introduction 10.2 Linkage analysis 10.3 Association analysis 10.4 Linkage disequilibrium 10.5 Quantitative trait locus (QTL) mapping in experimental crosses 10.6 Closing remarks References SECTION IV MOVING FROM ASSOCIATED GENES TO DISEASE ALLELES 11 Predictive functional analysis of polymorphisms: An overview Mary Plumpton and Michael R. Barnes 11.1 Introduction 11.2 Principles of predictive functional analysis of polymorphisms 11.3 The anatomy of promoter regions and regulatory elements 11.4 The anatomy of genes 11.5 Pseudogenes and regulatory mRNA 11.6 Analysis of novel regulatory elements and motifs in nucleotide sequences 11.7 Functional analysis on non-synonymous coding polymorphisms 11.8 Integrated tools for the functional analysis of genetic variation 11.9 A note of caution on the prioritization of in silico predictions for further laboratory investigations 11.10 Conclusions References 12 Functional in silico analysis of gene regulatory polymorphism Chaolin Zhang, Xiaoyue Zhao and Michael Q. Zhang 12.1 Introduction 12.2 Predicting regulatory regions 12.3 Modelling and predicting transcription factor-binding sites 12.4 Predicting regulatory elements for splicing regulation 12.5 Evaluating the functional importance of regulatory polymorphisms References 13 Amino-acid properties and consequences of substitutions Matthew J. Betts and Robert B. Russell 13.1 Introduction 13.2 Protein features relevant to amino-acid behaviour 13.3 Amino-acid classifications 13.4 Properties of the amino acids 13.5 Amino-acid quick reference 13.6 Studies of how mutations affect function 13.7 A summary of the thought process References 14 Non-coding RNA bioinformatics James Brown, Steve Deharo, Barry Dancis, Michael R. Barnes and Philippe Sanseau 14.1 Introduction 14.2 The non-coding (nc)RNA universe 14.3 Computational analysis of ncRNA 14.4 ncRNA variation in disease 14.5 Assessing the impact of variation in ncRNA 14.6 Data resources to support small ncRNA analysis 14.7 Conclusions References SECTION V ANALYSIS AT THE GENETIC AND GENOMIC DATA INTERFACE 15 What are microarrays? An introduction to microarray methods for measuring the iranscriptome Catherine A. Ball and Gavin Sherlock 15.1 Introduction 15.2 Principles of the application of microarray technology 15.3 Complementary approaches to microarray analysis 15.4 Differences between data repository and research database 15.5 Descriptions of freely available research database packages References 16 Combining quantitative traits and gene-expression data Elissa J. Chesler 16.1 Introduction: the genetic regulation of endophenotypes 16.2 Transcript abundance as a complex phenotype 16.3 Scaling up genetic analysis and mapping models for microarrays 16.4. Genetic correlation analysis 16.5. Systems genetic analysis 16.6. Using expression QTLs to identify candidate genes for the regulation of complex phenotypes 16.7. Conclusions References 17 Bioinformatics and cancer genetics Joel Greshock 17.1 Introduction 17.2 Cancer genomes 17.3 Approaches to studying cancer genetics 17.4 General resources for cancer genetics 17.5 Cancer genes and mutations 17.6 Copy number alterations in cancert 17.7 Loss of heterozygosity in cancer 17.8 Gene-expression data in cancer 17.9 Multiplatform gene target identification 17.10 The epigenetics of cancer 17.11 Tumour modelling 17.12 Conclusions References 18 Needle in a haystack? Dealing with 500 000 SNP genome scans Michael R. Barnes and Paul S. Derwent 18.1 Introduction 18.2 Genome scan analysis issues 18.3 Ultra-high-density genome-scanning technologies 18.4 Bioinformatics for genome-scan analysis 18.5 Conclusions References 19 A bioinformatics perspective on genetics in drug discovery and development Christopher D. Southan, Magnus Ulvsb¿ck and Michael R. Barnes 19.1 Introduction 19.2 Target genetics 19.3 Pharmacogenetics 19.4 Conclusions: toward ?personalized medicine? References Appendix I Appendix II Index
Library of Congress Subject Headings for this publication:
Genetics -- Data processing.
Bioinformatics.
Computational Biology -- methods.
Genomics -- methods.
Databases, Genetic.
Software.