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Bioinformatics for Geneticists: A Bioinformatics Primer for the Analysis of Genetic Data 2nd edition [Mīkstie vāki]

3.75/5 (13 ratings by Goodreads)
Edited by (GlaxoSmithKline Pharmaceuticals, UK)
  • Formāts: Paperback / softback, 576 pages, height x width x depth: 244x169x31 mm, weight: 964 g
  • Izdošanas datums: 09-Mar-2007
  • Izdevniecība: John Wiley & Sons Inc
  • ISBN-10: 0470026200
  • ISBN-13: 9780470026205
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  • Cena: 104,07 €
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  • Formāts: Paperback / softback, 576 pages, height x width x depth: 244x169x31 mm, weight: 964 g
  • Izdošanas datums: 09-Mar-2007
  • Izdevniecība: John Wiley & Sons Inc
  • ISBN-10: 0470026200
  • ISBN-13: 9780470026205
Citas grāmatas par šo tēmu:
Contributors from genetic and related biological sciences, most working for pharmaceutical companies, describe how fellow scientists can use bioinformatics to link their findings about genetic variations to biological functions and possible health problems. They begin by introducing bioinformatics to geneticists, then cover genes, genomes, and genetic variation data; genetic study design and analysis; moving from associated genes to disease alleles; and analysis at the genetic and genomic data interface. No date is noted for the first edition. Annotation ©2007 Book News, Inc., Portland, OR (booknews.com)

Praise from the reviews:

"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." CIRCGENETICS

"This book may really help to get geneticists and bioinformaticians on 'speaking-terms'... contains some essential reading for almost any person working in the field of molecular genetics." EUROPEAN JOURNAL OF HUMAN GENETICS 

"... an excellent resource... this book should ensure that any researcher's skill base is maintained." GENETICAL RESEARCH

“… 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.”  CIRCULATION: CARDIOVASCULAR GENETICS

A fully revised version of the successful First Edition, this one-stop reference book enables all geneticists to improve the efficiency of their research.

The 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, Bioinformatics for Geneticists, Second Edition 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.

Hallmark Features of the Second Edition:

  • Illustrates the value of bioinformatics as a constantly evolving avenue into novel approaches to study genetics
  • The only book specifically addressing the bioinformatics needs of geneticists
  • More than 50% of chapters are completely new contributions
  • Dramatically revised content in core areas of gene and genomic characterisation, pathway analysis, SNP functional analysis and statistical genetics
  • Focused on freely available tools and web-based approaches to bioinformatics analysis, suitable for novices and experienced researchers alike

Bioinformatics for Geneticists, Second Edition 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.

Recenzijas

" an excellent resourcethis book should ensure that any researchers skill base is maintained" (Genetical Research, 2007) "this book contains some essential reading for almost any person working in the field of molecular genetics." (European Journal Of Human Genetics, 2007)

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 agethis 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 Ive encountered that neatly introduces and summarizes many points Ive 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. (Circulation: Cardiovascular Genetics,  2008)

Foreword xi
Preface xv
Contributors xvii
Glossary xix
SECTION I AN INTRODUCTION TO BIOINFORMATICS FOR THE GENETICIST
1(32)
Bioinformatics challenges for the geneticist
3(14)
Michael R. Barnes
Introduction
3(1)
The role of bioinformatics in genetics research
4(1)
Genetics in the post-genome era
5(7)
Conclusions
12(5)
References
15(2)
Managing and manipulating genetic data
17(16)
Karl W. Broman
Simon C. Heath
Introduction
17(1)
Basic principles
18(2)
Data entry and storage
20(1)
Data manipulation
21(1)
Examples of code
22(8)
Resources
30(1)
Summary
31(2)
References
31(2)
SECTION II MASTERING GENES, GENOMES AND GENETIC VARIATION DATA
33(112)
The HapMap -- A haplotype map of the human genome
35(24)
Ellen M. Brown
Bryan J. Barratt
Introduction
35(3)
Accessing the data
38(4)
Application of HapMap data in association studies
42(12)
Future perspectives
54(5)
References
54(5)
Assembling a view of the human genome
59(26)
Colin A. M. Semple
Introduction
59(1)
Genomic sequence assembly
60(4)
Annotation from a distance: the generalities
64(6)
Annotation up close and personal: the specifics
70(8)
Annotation: the next generation
78(7)
References
80(5)
Finding, delineating and analysing genes
85(20)
Christopher Southan
Michael R. Barnes
Introduction
85(1)
Why learn to predict and analyse genes in the complete genome era?
86(2)
The evidence cascade for gene products
88(7)
Dealing with the complexities of gene models
95(2)
Locating known genes in the human genome
97(3)
Genome portal inspection
100(1)
Analysing novel genes
101(1)
Conclusions and prospects
102(3)
References
103(2)
Comparative genomics
105(40)
Martin S. Taylor
Richard R. Copley
Introduction
105(1)
The genomic landscape
106(3)
Concepts
109(4)
Practicalities
113(5)
Technology
118(14)
Applications
132(5)
Challenges and future directions
137(1)
Conclusion
138(7)
References
139(6)
SECTION III BIOINFORMATICS FOR GENETIC STUDY DESIGN AND ANALYSIS
145(102)
Identifying mutations in single gene disorders
147(18)
David P. Kelsell
Diana Blaydon
Charles A. Mein
Introduction
147(1)
Clinical ascertainment
147(1)
Genome-wide mapping of monogenic diseases
148(4)
The nature of mutation in monogenic diseases
152(8)
Considering epigenetic effects in mendelian traits
160(2)
Summary
162(3)
References
162(3)
From Genome Scan to Culprit Gene
165(20)
Ian C. Gray
Introduction
165(1)
Theoretical and practical considerations
166(10)
A stepwise approach to locus refinement and candidate gene identification
176(4)
Conclusion
180(1)
A list of the software tools and Web links mentioned in this chapter
181(4)
References
182(3)
Integrating Genetics, Genomics and Epigenomics to Identify Disease Genes
185(32)
Michael R. Barnes
Introduction
185(1)
Dealing with the (draft) human genome sequence
186(1)
Progressing loci of interest with genomic information
187(4)
In silico characterization of the IBD5 locus -- a case study
191(18)
Drawing together biological rationale -- hypothesis building
209(2)
Identification of potentially functional polymorphisms
211(1)
Conclusions
212(5)
References
213(4)
Tools for statistical genetics
217(30)
Aruna Bansal
Charlotte Vignal
Ralph McGinnis
Introduction
217(1)
Linkage analysis
217(6)
Association analysis
223(6)
Linkage disequilibrium
229(6)
Quantitative trait locus (QTL) mapping in experimental crosses
235(4)
Closing remarks
239(8)
References
241(6)
SECTION IV MOVING FROM ASSOCIATED GENES TO DISEASE ALLELES
247(122)
Predictive functional analysis of polymorphisms: An overview
249(32)
Mary Plumpton
Michael R. Barnes
Introduction
249(3)
Principles of predictive functional analysis of polymorphisms
252(4)
The anatomy of promoter regions and regulatory elements
256(2)
The anatomy of genes
258(8)
Pseudogenes and regulatory mRNA
266(1)
Analysis of novel regulatory elements and motifs in nucleotide sequences
266(2)
Functional analysis of non-synonymous coding polymorphisms
268(5)
Integrated tools for functional analysis of genetic variation
273(2)
A note of caution on the prioritization of in silico predictions for further laboratory investigation
275(1)
Conclusions
275(6)
References
276(5)
Functional in silico analysis of gene regulatory polymorphism
281(30)
Chaolin Zhang
Xiaoyue Zhao
Michael Q. Zhang
Introduction
281(1)
Predicting regulatory regions
282(6)
Modelling and predicting transcription factor-binding sites
288(7)
Predicting regulatory elements for splicing regulation
295(5)
Evaluating the functional importance of regulatory polymorphisms
300(11)
References
302(9)
Amino-acid properties and consequences of substitutions
311(32)
Matthew J. Betts
Robert B. Russell
Introduction
311(1)
Protein features relevant to amino-acid behaviour
312(4)
Amino-acid classifications
316(2)
Properties of the amino acids
318(3)
Amino-acid quick reference
321(13)
Studies of how mutations affect function
334(5)
A summary of the thought process
339(4)
References
340(3)
Non-coding RNA bioinformatics
343(26)
James R. Brown
Steve Deharo
Barry Dancis
Michael R. Barnes
Philippe Sanseau
Introduction
343(1)
The non-coding (nc) RNA universe
344(5)
Computational analysis of ncRNA
349(7)
ncRNA variation in disease
356(6)
Assessing the impact of variation in ncRNA
362(1)
Data resources to support small ncRNA analysis
363(1)
Conclusions
363(6)
References
364(5)
SECTION V ANALYSIS AT THE GENETIC AND GENOMIC DATA INTERFACE
369(160)
What are microarrays?
371(18)
Catherine A. Ball
Gavin Sherlock
Introduction
371(2)
Principles of the application of microarray technology
373(4)
Complementary approaches to microarray analysis
377(1)
Differences between data repository and research database
377(1)
Descriptions of freely available research database packages
377(12)
References
385(4)
Combining quantitative trait and gene-expression data
389(24)
Elissa J. Chesler
Introduction: the genetic regulation of endophenotypes
389(1)
Transcript abundance as a complex phenotype
390(4)
Scaling up genetic analysis and mapping models for microarrays
394(3)
Genetic correlation analysis
397(3)
Systems genetic analysis
400(3)
Using expression QTLs to identify candidate genes for the regulation of complex phenotypes
403(5)
Conclusions
408(5)
References
408(5)
Bioinformatics and cancer genetics
413(34)
Joel Greshock
Introduction
413(1)
Cancer genomes
414(1)
Approaches to studying cancer genetics
415(3)
General resources for cancer genetics
418(2)
Cancer genes and mutations
420(5)
Copy number alterations in cancer
425(6)
Loss of heterozygosity in cancer
431(1)
Gene-expression data in cancer
432(3)
Multiplatform gene target identification
435(3)
The epigenetics of cancer
438(1)
Tumour modelling
438(1)
Conclusions
439(8)
References
439(8)
Needle in a haystack? Dealing with 500 000 SNP genome scans
447(48)
Michael R. Barnes
Paul S. Derwent
Introduction
447(2)
Genome scan analysis issues
449(10)
Ultra-high-density genome-scanning technologies
459(10)
Bioinformatics for genome scan analysis
469(20)
Conclusions
489(6)
References
490(5)
A bioinformatics perspective on genetics in drug discovery and development
495(34)
Christopher Southan
Magnus Ulvsback
Michael R. Barnes
Introduction
495(3)
Target genetics
498(10)
Pharmacogenetics (PGx)
508(17)
Conclusions: toward `personalized medicine'
525(4)
References
525(4)
Appendix I 529(2)
Appendix II 531(6)
Index 537


Michael R. Barnes: Bioinformatics, GlaxoSmithKline Pharmaceuticals, UK