Bioinformatics for Geneticists

Name: Bioinformatics for Geneticists | A Bioinformatics Primer for the Analysis of Genetic Data
Brand: Wiley
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A Bioinformatics Primer for the Analysis of Genetic Data

Michael R. Barnes(Editor)

Wiley (Publisher)

2nd Edition

Published on 13. March 2007

576 pages

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978-0-470-05917-3 (ISBN)

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Praise from the reviews: "Without reservation, I endorse this text as the bestresource I've encountered that neatly introduces and summarizesmany points I've learned through years of experience. Thegems of truth found in this book will serve well those who wish toapply bioinformatics in their daily work, as well as help themadvise others in this capacity." CIRCGENETICS "This book may really help to get geneticists andbioinformaticians on 'speaking-terms'... contains someessential reading for almost any person working in the field ofmolecular genetics." EUROPEAN JOURNAL OF HUMANGENETICS "... an excellent resource... this book should ensure thatany researcher's skill base is maintained." GENETICALRESEARCH "... one of the best available and most accessibletexts on bioinformatics and genetics in the postgenome age...The writing is clear, with succinct subsections within eachchapter....Without reservation, I endorse this text as the bestresource I've encountered that neatly introduces andsummarizes many points I've learned through years ofexperience. The gems of truth found in this book will serve wellthose who wish to apply bioinformatics in their daily work, as wellas help them advise others in this capacity." CIRCULATION: CARDIOVASCULAR GENETICS A fully revised version of the successful First Edition, thisone-stop reference book enables all geneticists to improve theefficiency of their research. The study of human genetics is moving into a challenging newera. New technologies and data resources such as the HapMap areenabling genome-wide studies, which could potentially identify mostcommon genetic determinants of human health, disease and drugresponse. With these tremendous new data resources at hand, morethan ever care is required in their use. Faced with the sheervolume of genetics and genomic data, bioinformatics is essential toavoid drowning true signal in noise. Considering these challenges,Bioinformatics for Geneticists, Second Edition works atmultiple levels: firstly, for the occasional user who simply wantsto extract or analyse specific data; secondly, at the level of theadvanced user providing explanations of how and why a tool worksand how it can be used to greatest effect. Finally experts fromfields allied to genetics give insight into the best genomics toolsand data to enhance a genetic experiment. Hallmark Features of the Second Edition: * Illustrates the value of bioinformatics as a constantlyevolving avenue into novel approaches to study genetics * The only book specifically addressing the bioinformatics needsof geneticists * More than 50% of chapters are completely new contributions * Dramatically revised content in core areas of gene and genomiccharacterisation, pathway analysis, SNP functional analysis andstatistical genetics * Focused on freely available tools and web-based approaches tobioinformatics analysis, suitable for novices and experiencedresearchers alike Bioinformatics for Geneticists, SecondEdition describes the key bioinformatics and geneticanalysis processes that are needed to identify human geneticdeterminants. The book is based upon the combined practicalexperience of domain experts from academic and industrial researchenvironments and is of interest to a broad audience, includingstudents, researchers and clinicians working in the human geneticsdomain.

Reviews / Votes

" ...an excellent resource...this book should ensure thatany researcher's skill base is maintained" (GeneticalResearch, 2007) "...this book contains some essential reading for almost anyperson working in the field of molecular genetics." (EuropeanJournal Of Human Genetics, 2007) "Over 19 chapters, the authors cover an impressiveterrain. The focus is mainly on human genetics and genomics, withresearch in other species also presented, particularly where itsupports and advances our understanding of human genetics.Although a thoughtful discussion of the relevant literature andtechniques is found in each chapter, the book is not overlytechnical and does not present advanced mathematical, statistical,or genetic concepts in great depth. Instead, focus is on practicalapplications, available tools, software, and databases, and thepresentation supporting real world research examples. The endresult is one of the best available and most accessible texts onbioinformatics and genetics in the postgenome age...this bookin its current edition still serves as one of the best resourcesavailable, particularly in chapters on noncoding RNAs,pharmacogenetics, and drug discovery, microarrays/gene expression,regulatory polymorphisms, and the potential impacts of amino acidchanges. The writing is clear, with succinct subsections withineach chapter....Without reservation, I endorse this text as thebest resource I've encountered that neatly introduces andsummarizes many points I've learned through years ofexperience. The gems of truth found in this book will serve wellthose who wish to apply bioinformatics in their daily work, as wellas help them advise others in thiscapacity." (Circulation: CardiovascularGenetics, 2008)

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Intro
Bioinformatics for Geneticists
Contents
Foreword
Preface
Contributors
Glossary
Section I An Introduction to Bioinformatics for the Geneticist
1 Bioinformatics Challenges for the Geneticist
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 17
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
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
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
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
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
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
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
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 genetics
10.1 Introduction
10.2 Linkage Analysis
10.3 Association Analysis
10.4 Linkage disequilibrium
10.5 Quantitative Trait Locus (QTL) Rapping 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
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 of Non-Synonymous Coding Polymorphisms
11.8 Integrated Tools for Functional Analysis of Genetic Variation
11.9 A Note of Caution on the Prioritization of in Silico Predictions for Further Laboratory Investigation
11.10 Conclusions
References
12 Functional in Silico Analysis of Gene Regulatory Polymorphism
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
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
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?
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 Trait and Gene-Expression Data
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
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 Cancer
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
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
19.1 Introduction
19.2 Target Genetics
19.3 Pharmacogenetics (PGx)
19.4 Conclusions: Toward 'Personalized Medicine'
References
Appendix I
Appendix II
Index

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