{"product_id":"bioinformatics-for-geneticists-isbn-9780470026205","title":"Bioinformatics for Geneticists","description":"\u003cb\u003ePraise from the reviews:\u003c\/b\u003e  \u003cp\u003e\u003ci\u003e\"Without reservation, I endorse this text as the best resource I've encountered that neatly introduces and summarizes many points I've learned through years of experience.  The gems of truth found in this book will serve well those who wish to apply bioinformatics in their daily work, as well as help them advise others in this capacity.\"\u003c\/i\u003e CIRCGENETICS\u003c\/p\u003e \u003cp\u003e\u003ci\u003e\"This book may really help to get geneticists and bioinformaticians on 'speaking-terms'... co\u003c\/i\u003e\u003ci\u003entains some essential reading for almost any person working in the field of molecular genetics.\"\u003c\/i\u003e EUROPEAN JOURNAL OF HUMAN GENETICS \u003c\/p\u003e \u003cp\u003e\u003ci\u003e\"... an excellent resource... this book should ensure that any researcher's skill base is maintained.\"\u003c\/i\u003e GENETICAL RESEARCH\u003c\/p\u003e \u003cp\u003e\u003ci\u003e“… one of the best available and most accessible texts on bioinformatics and genetics in the postgenome age… The writing is clear, with succinct subsections within each chapter….Without reservation, I endorse this text as the best resource I’ve encountered that neatly introduces and summarizes many points I’ve learned through years of experience. The gems of truth found in this book will serve well those who wish to apply bioinformatics in their daily work, as well as help them advise others in this capacity.”\u003c\/i\u003e  CIRCULATION: CARDIOVASCULAR GENETICS\u003c\/p\u003e \u003cp\u003eA fully revised version of the successful First Edition, this one-stop reference book enables all geneticists to improve the efficiency of their research.\u003c\/p\u003e \u003cp\u003eThe study of human genetics is moving into a challenging new era. New technologies and data resources such as the HapMap are enabling genome-wide studies, which could potentially identify most common genetic determinants of human health, disease and drug response. With these tremendous new data resources at hand, more than ever care is required in their use. Faced with the sheer volume of genetics and genomic data, bioinformatics is essential to avoid drowning true signal in noise. Considering these challenges, \u003ci\u003eBioinformatics for Geneticists, Second Edition\u003c\/i\u003e works at multiple levels: firstly, for the occasional user who simply wants to extract or analyse specific data; secondly, at the level of the advanced user providing explanations of how and why a tool works and how it can be used to greatest effect. Finally experts from fields allied to genetics give insight into the best genomics tools and data to enhance a genetic experiment.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eHallmark Features of the Second Edition:\u003c\/b\u003e\u003c\/p\u003e \u003cul\u003e \u003cli\u003eIllustrates the value of bioinformatics as a constantly evolving avenue into novel approaches to study genetics\u003c\/li\u003e \u003cli\u003eThe only book specifically addressing the bioinformatics needs of geneticists\u003c\/li\u003e \u003cli\u003eMore than 50% of chapters are completely new contributions\u003c\/li\u003e \u003cli\u003eDramatically revised content in core areas of gene and genomic characterisation, pathway analysis, SNP functional analysis and statistical genetics\u003c\/li\u003e \u003cli\u003eFocused on freely available tools and web-based approaches to bioinformatics analysis, suitable for novices and experienced researchers alike\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eBioinformatics for Geneticists, Second Edition\u003c\/i\u003e describes the key bioinformatics and genetic analysis processes that are needed to identify human genetic determinants. The book is based upon the combined practical experience of domain experts from academic and industrial research environments and is of interest to a broad audience, including students, researchers and clinicians working in the human genetics domain.\u003c\/p\u003e  Foreword.  \u003cp\u003ePreface.\u003c\/p\u003e \u003cp\u003eContributors.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eSECTION I AN INTRODUCTION TO BIOINFORMATICS FOR THE GENETICIST.\u003c\/p\u003e \u003cp\u003e1 Bioinformatics challenges for the geneticist (\u003ci\u003eMichael R. Barnes).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction.\u003c\/p\u003e \u003cp\u003e1.2 The role of bioinformatics in genetics research.\u003c\/p\u003e \u003cp\u003e1.3 Genetics in the post-genome era.\u003c\/p\u003e \u003cp\u003e1.4 Conclusions.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e2 Managing and manipulating genetic data (\u003ci\u003eKarl W. Broman and Simon C. Heath).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction.\u003c\/p\u003e \u003cp\u003e2.2 Basic principles.\u003c\/p\u003e \u003cp\u003e2.3 Data entry and storage.\u003c\/p\u003e \u003cp\u003e2.4 Data manipulation.\u003c\/p\u003e \u003cp\u003e2.5 Examples of code.\u003c\/p\u003e \u003cp\u003e2.6 Resources.\u003c\/p\u003e \u003cp\u003e2.7 Summary.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003eSECTION II MASTERING GENES, GENOMES AND GENETIC VARIATION DATA.\u003c\/p\u003e \u003cp\u003e3 The HapMap – A haplotype map of the human genome (\u003ci\u003eEllen M. Brown and Bryan J. Barratt).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction.\u003c\/p\u003e \u003cp\u003e3.2 Accessing the data.\u003c\/p\u003e \u003cp\u003e3.3 Application of HapMap data in association studies.\u003c\/p\u003e \u003cp\u003e3.4 Future Perspectives.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e4 Assembling a view of the human genome (\u003ci\u003eColin A. M. Semple).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction.\u003c\/p\u003e \u003cp\u003e4.2 Genomic sequence assembly.\u003c\/p\u003e \u003cp\u003e4.3 Annotation from a distance: the generalities.\u003c\/p\u003e \u003cp\u003e4.4 Annotation up close and personal: the specifics.\u003c\/p\u003e \u003cp\u003e4.5 Annotation: the next generation.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e5 Finding, delineating and analysing genes (\u003ci\u003eChristopher Southan and Michael R. Barnes).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction.\u003c\/p\u003e \u003cp\u003e5.2 Why learn to predict and analyse genes in the complete genome era?\u003c\/p\u003e \u003cp\u003e5.3 The evidence cascade for gene products.\u003c\/p\u003e \u003cp\u003e5.4 Dealing with the complexities of gene models.\u003c\/p\u003e \u003cp\u003e5.5 Locating known genes in the human genome.\u003c\/p\u003e \u003cp\u003e5.6 Genome portal inspection.\u003c\/p\u003e \u003cp\u003e5.7 Analysing novel genes.\u003c\/p\u003e \u003cp\u003e5.8 Conclusions and prospects.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e6 Comparative genomics (\u003ci\u003eMartin S. Taylor and Richard R. Copley).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction.\u003c\/p\u003e \u003cp\u003e6.2 The Genomic landscape.\u003c\/p\u003e \u003cp\u003e6.3 Concepts.\u003c\/p\u003e \u003cp\u003e6.4 Practicalities.\u003c\/p\u003e \u003cp\u003e6.5 Technology.\u003c\/p\u003e \u003cp\u003e6.6 Applications.\u003c\/p\u003e \u003cp\u003e6.7 Challenges and future directions.\u003c\/p\u003e \u003cp\u003e6.8 Conclusion.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003eSECTION III BIOINFORMATICS FOR GENETIC STUDY DESIGN AND ANALYSIS.\u003c\/p\u003e \u003cp\u003e7 Identifying mutations in single gene disorders (\u003ci\u003eDavid P. Kelsell, Diana Blaydon and Charles A. Mein).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction.\u003c\/p\u003e \u003cp\u003e7.2 Clinical Ascertainment.\u003c\/p\u003e \u003cp\u003e7.3 Genome-wide mapping of monogenic diseases.\u003c\/p\u003e \u003cp\u003e7.4 The nature of mutation in monogenic diseases.\u003c\/p\u003e \u003cp\u003e7.5 Considering epigenetic effects in mendelian traits.\u003c\/p\u003e \u003cp\u003e7.6 Summary.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e8 From Genome Scan Culprit Gene (\u003ci\u003eIan C. Gray).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction.\u003c\/p\u003e \u003cp\u003e8.2 Theoretical and practical considerations.\u003c\/p\u003e \u003cp\u003e8.3 A stepwise approach to locus refinement and candidate gene identification.\u003c\/p\u003e \u003cp\u003e8.4 Conclusion.\u003c\/p\u003e \u003cp\u003e8.5 A list of the software tools and Web links mentioned in this chapter.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e9 Integrating Genetics, Genomics and Epigenomics to Identify.\u003c\/p\u003e \u003cp\u003eDisease Genes (\u003ci\u003eMichael R. Barnes).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction.\u003c\/p\u003e \u003cp\u003e9.2 Dealing with the (draft) human genome sequence.\u003c\/p\u003e \u003cp\u003e9.3 Progressing loci of interest with genomic information.\u003c\/p\u003e \u003cp\u003e9.4 \u003ci\u003eIn silico\u003c\/i\u003e characterization of the IBD5 locus – a case study.\u003c\/p\u003e \u003cp\u003e9.5 Drawing together biological rationale – hypothesis building.\u003c\/p\u003e \u003cp\u003e9.6 Identification of potentially functional polymorphisms.\u003c\/p\u003e \u003cp\u003e9.7 Conclusions.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e10 Tools for statistical genetics (\u003ci\u003eAruna Bansal, Charlotte Vignal and Ralph McGinnis).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction.\u003c\/p\u003e \u003cp\u003e10.2 Linkage analysis.\u003c\/p\u003e \u003cp\u003e10.3 Association analysis.\u003c\/p\u003e \u003cp\u003e10.4 Linkage disequilibrium.\u003c\/p\u003e \u003cp\u003e10.5 Quantitative trait locus (QTL) mapping in experimental crosses.\u003c\/p\u003e \u003cp\u003e10.6 Closing remarks.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003eSECTION IV MOVING FROM ASSOCIATED GENES TO DISEASE ALLELES.\u003c\/p\u003e \u003cp\u003e11 Predictive functional analysis of polymorphisms: An overview (\u003ci\u003eMary Plumpton and Michael R. Barnes).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction.\u003c\/p\u003e \u003cp\u003e11.2 Principles of predictive functional analysis of polymorphisms.\u003c\/p\u003e \u003cp\u003e11.3 The anatomy of promoter regions and regulatory elements.\u003c\/p\u003e \u003cp\u003e11.4 The anatomy of genes.\u003c\/p\u003e \u003cp\u003e11.5 Pseudogenes and regulatory mRNA.\u003c\/p\u003e \u003cp\u003e11.6 Analysis of novel regulatory elements and motifs in.\u003c\/p\u003e \u003cp\u003enucleotide sequences.\u003c\/p\u003e \u003cp\u003e11.7 Functional analysis of non-synonymous coding polymorphisms.\u003c\/p\u003e \u003cp\u003e11.8 Integrated tools for functional analysis of genetic variation.\u003c\/p\u003e \u003cp\u003e11.9 A note of caution on the prioritization of \u003ci\u003ein silico\u003c\/i\u003e predictions for.\u003c\/p\u003e \u003cp\u003efurther laboratory investigation.\u003c\/p\u003e \u003cp\u003e11.10 Conclusions.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e12 Functional \u003ci\u003ein silico\u003c\/i\u003e analysis of gene regulatory polymorphism (\u003ci\u003eChaolin Zhang, Xiaoyue Zhao, Michael Q. Zhang).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction.\u003c\/p\u003e \u003cp\u003e12.2 Predicting regulatory regions.\u003c\/p\u003e \u003cp\u003e12.3 Modelling and predicting transcription factor-binding sites.\u003c\/p\u003e \u003cp\u003e12.4 Predicting regulatory elements for splicing regulation.\u003c\/p\u003e \u003cp\u003e12.5 Evaluating the functional importance of.\u003c\/p\u003e \u003cp\u003eregulatory polymorphisms.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e13 Amino-acid properties and consequences of substitutions (\u003ci\u003eMatthew J. Betts and Robert B. Russell).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction.\u003c\/p\u003e \u003cp\u003e13.2 Protein features relevant to amino-acid behaviour.\u003c\/p\u003e \u003cp\u003e13.3 Amino-acid classifications.\u003c\/p\u003e \u003cp\u003e13.4 Properties of the amino acids.\u003c\/p\u003e \u003cp\u003e13.5 Amino-acid quick reference.\u003c\/p\u003e \u003cp\u003e13.6 Studies of how mutations affect function.\u003c\/p\u003e \u003cp\u003e13.7 A summary of the thought process.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e14 Non-coding RNA bioinformatics (\u003ci\u003eJames Brown, Steve Deharo, Barry Dancis, Michael R. Barnes and Philippe Sanseau).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction.\u003c\/p\u003e \u003cp\u003e14.2 The non-coding (nc) RNA universe.\u003c\/p\u003e \u003cp\u003e14.3 Computational analysis of ncRNA.\u003c\/p\u003e \u003cp\u003e14.4 ncRNA variation in disease.\u003c\/p\u003e \u003cp\u003e14.5 Assessing the impact of variation in ncRNA.\u003c\/p\u003e \u003cp\u003e14.6 Data resources to support small ncRNA analysis.\u003c\/p\u003e \u003cp\u003e14.7 Conclusions.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003eSECTION V ANALYSIS AT THE GENETIC AND GENOMIC DATA INTERFACE.\u003c\/p\u003e \u003cp\u003e15 What are microarrays? (\u003ci\u003eCatherine A. Ball and Gavin Sherlock).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction.\u003c\/p\u003e \u003cp\u003e15.2 Principles of the application of microarray technology.\u003c\/p\u003e \u003cp\u003e15.3 Complementary approaches to microarray analysis.\u003c\/p\u003e \u003cp\u003e15.4 Differences between data repository and research database.\u003c\/p\u003e \u003cp\u003e15.5 Descriptions of freely available research database packages.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e16 Combining quantitative trait and gene-expression data (\u003ci\u003eElissa J. Chesler).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction: the genetic regulation of endophenotypes.\u003c\/p\u003e \u003cp\u003e16.2 Transcript abundance as a complex phenotype.\u003c\/p\u003e \u003cp\u003e16.3 Scaling up genetic analysis and mapping models for microarrays.\u003c\/p\u003e \u003cp\u003e16.4 Genetic correlation analysis.\u003c\/p\u003e \u003cp\u003e16.5 Systems genetic analysis.\u003c\/p\u003e \u003cp\u003e16.6 Using expression QTLs to identify candidate genes for the regulation of complex phenotypes.\u003c\/p\u003e \u003cp\u003e16.7 Conclusions.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e17 Bioinformatics and cancer genetics (\u003ci\u003eJoel Greshock).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17.1 Introduction.\u003c\/p\u003e \u003cp\u003e17.2 Cancer genomes.\u003c\/p\u003e \u003cp\u003e17.3 Approaches to studying cancer genetics.\u003c\/p\u003e \u003cp\u003e17.4 General resources for cancer genetics.\u003c\/p\u003e \u003cp\u003e17.5 Cancer genes and mutations.\u003c\/p\u003e \u003cp\u003e17.6 Copy number alterations in cancer.\u003c\/p\u003e \u003cp\u003e17.7 Loss of heterozygosity in cancer.\u003c\/p\u003e \u003cp\u003e17.8 Gene-expression data in cancer.\u003c\/p\u003e \u003cp\u003e17.9 Multiplatform gene target identification.\u003c\/p\u003e \u003cp\u003e17.10 The epigenetics of cancer.\u003c\/p\u003e \u003cp\u003e17.11 Tumour modelling.\u003c\/p\u003e \u003cp\u003e17.12 Conclusions.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e18 Needle in a haystack? dealing with 500 SNP genome scans (\u003ci\u003eMichael R. Barnes and Paul S. Derwent).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18.1 Introduction.\u003c\/p\u003e \u003cp\u003e18.2 Genome scan analysis issues.\u003c\/p\u003e \u003cp\u003e18.3 Ultra-high-density genome-scanning technologies.\u003c\/p\u003e \u003cp\u003e18.4 Bioinformatics for genome scan analysis.\u003c\/p\u003e \u003cp\u003e18.5 Conclusions.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e19 A bioinformatics perspective on genetics in drug discovery and development (\u003ci\u003eChristopher D. Southan, Magnus Ulvsb¨ack and Michael R. Barnes).\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e19.1 Introduction.\u003c\/p\u003e \u003cp\u003e19.2 Target genetics.\u003c\/p\u003e \u003cp\u003e19.3 Pharmacogenetics (PGx).\u003c\/p\u003e \u003cp\u003e19.4 Conclusions: toward ‘personalized medicine’.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003eAppendix I.\u003c\/p\u003e \u003cp\u003eAppendix II.\u003c\/p\u003e \u003cp\u003eIndex.\u003c\/p\u003e  \" …an excellent resource…this book should ensure that any researcher’s skill base is maintained\" (\u003ci\u003eGenetical Research\u003c\/i\u003e, 2007)  \u003cp\u003e\"…this book contains some essential reading for almost any person working in the field of molecular genetics.\" (\u003ci\u003eEuropean Journal Of Human Genetics\u003c\/i\u003e, 2007)\u003c\/p\u003e \u003cp\u003e“Over 19 chapters, the authors cover an impressive terrain. The focus is mainly on human genetics and genomics, with research in other species also presented, particularly where it supports  and advances our understanding of human genetics. Although a thoughtful discussion of the relevant literature and techniques is found in each chapter, the book is not overly technical and does not present advanced mathematical, statistical, or genetic concepts in great depth. Instead, focus is on practical applications, available tools, software, and databases, and the presentation supporting real world research examples. The end result is one of the best available and most accessible texts on bioinformatics and genetics in the postgenome age…this book in its current edition still serves as one of the best resources available, particularly in chapters on noncoding RNAs, pharmacogenetics, and drug discovery, microarrays\/gene expression, regulatory polymorphisms, and the potential impacts of amino acid changes. The writing is clear, with succinct subsections within each chapter….Without reservation, I endorse this text as the best resource I’ve encountered that neatly introduces and summarizes many points I’ve learned through years of experience. The gems of truth found in this book will serve well those who wish to apply bioinformatics in their daily work, as well as help them advise others in this capacity.” (\u003ci\u003eCirculation: Cardiovascular Genetics, \u003c\/i\u003e 2008)\u003c\/p\u003e \u003ci\u003eMichael R. Barnes: Bioinformatics, GlaxoSmithKline Pharmaceuticals, UK\u003c\/i\u003e  The study of human genetics is moving into a challenging new era of discovery. New technologies and data resources such as the HapMap, are enabling genome-wide genetic association studies which could potentially identify most common (and some rarer) genetic determinants of human health, disease and drug response. Although the tools may be at hand, more than ever care is required in their use. Faced with the sheer volume of data threatening to drown true signal in noise, bioinformatics is now assuming a central role in genetic study design, analysis and interpretation.  \u003cp\u003eCoupled with the advances in genetics, new insights are emerging into additional layers of complexity in genome function, for example the role of micro RNA in control of gene translation and new \u003ci\u003ecis\u003c\/i\u003e-regulatory elements identified by genetic analysis of gene expression. Understanding genetics will require an effective synthesis of this complexity and, as this book shows, this is simply not possible without bioinformatics.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eBioinformatics for Geneticists\u003c\/i\u003e seeks to describe the key bioinformatics and genetic analysis processes that are needed to identify human genetic determinants. The book is based upon the combined practical experience of domain experts from academic and industrial research environments and should be of interest to a broad audience, including students, researchers and clinicians working in the human genetics domain.\u003c\/p\u003e \u003cul\u003e \u003cli\u003e \u003cdiv\u003eMore than 50% of chapters are completely new contributions, covering data manipulation and management, the HapMap, micro RNA, comparative genomics, epigenetics, cancer genetics, genetic analysis of gene expression, high-density genome scan analysis, pharmacogenetics and drug discovery.\u003c\/div\u003e \u003c\/li\u003e \u003cli\u003e \u003cdiv\u003eDramatically revised content in core areas of gene and genomic characterization, pathway analysis, SNP functional analysis and statistical genetics.\u003c\/div\u003e \u003c\/li\u003e \u003cli\u003e \u003cdiv\u003eFocused on freely available tools and web-based approaches to bioinformatics analysis, suitable for novices and experienced researchers alike.\u003c\/div\u003e \u003c\/li\u003e \u003cli\u003e \u003cdiv\u003eThe only book specifically addressing the bioinformatics needs of geneticists.\u003c\/div\u003e \u003c\/li\u003e \u003c\/ul\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47988821328101,"sku":"NP9780470026205","price":133.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780470026205.jpg?v=1761781710","url":"https:\/\/k12savings.com\/es\/products\/bioinformatics-for-geneticists-isbn-9780470026205","provider":"K12savings","version":"1.0","type":"link"}