Bioinformatics for geneticists

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Publication Information:

Chichester, England: Wiley, 2003

ISBN:

9780470843932

Subject Term:

Bioinformatics

Genetics -- Data processing

Added Author:

Barnes, Michael R.

Gray, Ian C.

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Library	Item Barcode	Call Number	Material Type	Item Category 1	Status
Searching... PSZ JB	30000010074728	QH430 B56 2003	Open Access Book	Book	Searching... Unknown

This timely book illustrates the value of bioinformatics, not simply as a set of tools but rather as a science increasingly essential to navigate and manage the host of information generated by genomics and the availability of completely sequenced genomes. Bioinformatics can be used at all stages of genetics research: to improve study design, to assist in candidate gene identification, to aid data interpretation and management and to shed light on the molecular pathology of disease-causing mutations. Written specifically for geneticists, this book explains the relevance of bioinformatics showing how it may be used to enhance genetic data mining and markedly improve genetic analysis.

Michael R. Barnes and Ian C. GrayMichael R. Barnes and Christopher SouthanMichael R. BarnesChristopher SouthanColin A. SempleJudith A. Blake and Janan Eppig and Carol J. BultMichael R. BarnesIan C. GrayMichael R. BarnesEllen Vieux and Gabor Marth and Pui KwokAruna Bansal and Peter R. Boyd and Ralph McGinnisMichael R. BarnesThomas WernerMatthew J. Betts and Robert B. RussellAntoine H. C. van Kampen and Jan M. Ruijter and Barbera D. C. van Schaik and Huib N. Caron and Rogier VersteegJerome Wojcik and Alexandre HamburgerMichael R. Barnes and Ian C. Gray

List of contributors	p. xi
Foreword	p. xiii
Section I. An Introduction to Bioinformatics for the Geneticist	p. 1
Chapter 1 Introduction: The Role of Genetic Bioinformatics	p. 3
1.1 Introduction	p. 3
1.2 Genetics in the post-genome era--the role of bioinformatics	p. 6
1.3 Knowledge management and expansion	p. 6
1.4 Data management and mining	p. 6
1.5 Genetic study designs	p. 8
1.6 Physical locus analysis	p. 12
1.7 Selecting candidate genes for analysis	p. 14
1.8 Progressing from candidate gene to disease-susceptibility gene	p. 14
1.9 Comparative genetics and genomics	p. 15
1.10 Conclusions	p. 17
References	p. 18
Chapter 2 Internet Resources for the Geneticist	p. 21
2.1 Introduction	p. 22
2.2 Sub-division of biological data on the internet	p. 23
2.3 Searching the internet for genetic information	p. 24
2.4 Which web search engine?	p. 24
2.5 Search syntax: the mathematics of search engine use	p. 26
2.6 Boolean searching	p. 27
2.7 Searching scientific literature--getting to 'state of the art'	p. 28
2.8 Searching full-text journals	p. 29
2.9 Searching the heart of the biological internet--sequences and genomic data	p. 30
2.10 Nucleotide and protein sequence databases	p. 30
2.11 Biological sequence databases--primary and secondary	p. 31
2.12 Conclusions	p. 36
References	p. 37
Chapter 3 Human Genetic Variation: Databases and Concepts	p. 39
3.1 Introduction	p. 40
3.2 Forms and mechanisms of genetic variation	p. 43
3.3 Databases of human genetic variation	p. 50
3.4 SNP databases	p. 51
3.5 Mutation databases	p. 57
3.6 Genetic marker and microsatellite databases	p. 60
3.7 Non-nuclear and somatic mutation databases	p. 61
3.8 Tools for SNP and mutation visualization--the genomic context	p. 63
3.9 Tools for SNP and mutation visualization--the gene context	p. 63
3.10 Conclusions	p. 67
References	p. 67
Chapter 4 Finding, Delineating and Analysing Genes	p. 71
4.1 Introduction	p. 71
4.2 The evidence cascade for gene products	p. 72
4.3 Shortcomings of the standard gene model	p. 75
4.4 Locating known genes on the Golden Path	p. 76
4.5 Gene portal inspection	p. 79
4.6 Locating genes which are not present in the Golden Path	p. 80
4.7 Analysing a novel gene	p. 81
4.8 Comprehensive database searching	p. 88
4.9 Conclusions and prospects	p. 90
References	p. 90
Section II. The Impact of Complete Genome Sequences on Genetics	p. 93
Chapter 5 Assembling a View of the Human Genome	p. 95
5.1 Introduction	p. 95
5.2 Genomic sequence assembly	p. 98
5.3 Annotation from a distance: the generalities	p. 101
5.4 Annotation up close and personal: the specifics	p. 105
5.5 Annotation: the next generation	p. 113
Acknowledgements	p. 114
References	p. 114
Chapter 6 Mouse and Rat Genome Informatics	p. 119
6.1 Introduction	p. 120
6.2 The model organism databases for mouse and rat	p. 122
6.3 Mouse genetic and physical maps	p. 124
6.4 Rat genetic and physical maps	p. 127
6.5 Genome sequence resources	p. 128
6.6 Comparative genomics	p. 131
6.7 From genotype to phenotype	p. 132
6.8 Functional genomics	p. 135
6.9 Rodent disease models	p. 137
6.10 Summary	p. 137
Acknowledgements	p. 138
References	p. 138
Chapter 7 Genetic and Physical Map Resources--An Integrated View	p. 143
7.1 Introduction	p. 144
7.2 Genetic maps	p. 145
7.3 Physical maps	p. 148
7.4 Physical contig maps	p. 151
7.5 The role of physical and genetic maps in draft sequence curation	p. 152
7.6 The human genome sequence--the ultimate physical map?	p. 153
7.7 QC of genomic DNA--resolution of marker order and gap sizes	p. 154
7.8 Tools and databases for map analysis and integration	p. 155
7.9 Conclusions	p. 159
References	p. 160
Section III. Bioinformatics for Genetic Study Design	p. 163
Chapter 8 From Linkage Peak to Culprit Gene: Following Up Linkage Analysis of Complex Phenotypes with Population-based Association Studies	p. 165
8.1 Introduction	p. 165
8.2 Theoretical and practical considerations	p. 166
8.3 A practical approach to locus refinement and candidate gene identification	p. 173
8.4 Conclusion	p. 176
Acknowledgements	p. 176
References	p. 177
Chapter 9 Genetic Studies from Genomic Sequence	p. 179
9.1 Introduction	p. 180
9.2 Defining the locus	p. 180
9.3 Case study 1: Identification and extraction of a genomic sequence between two markers	p. 184
9.4 Case study 2: Checking the integrity of a genomic sequence between two markers	p. 185
9.5 Case study 3: Definition of known and novel genes across a genomic region	p. 188
9.6 Case study 4: Candidate gene selection--building biological rationale around genes	p. 190
9.7 Case study 5: Known and novel marker identification	p. 195
9.8 Case study 6: Genetic/physical locus characterization and marker panel design	p. 199
9.9 Conclusions	p. 201
References	p. 201
Chapter 10 SNP Discovery and PCR-based Assay Design: From In Silico Data to the Laboratory Experiment	p. 203
10.1 Introduction	p. 204
10.2 SNP identification	p. 205
10.3 PCR primer design	p. 207
10.4 Broader PCR assay design issues	p. 208
10.5 Primer selection	p. 210
10.6 Problems related to SNP assay validation	p. 212
10.7 Conclusion	p. 213
References	p. 213
Chapter 11 Tools for Statistical Analysis of Genetic Data	p. 217
11.1 Introduction	p. 218
11.2 Linkage analysis	p. 218
11.3 Association analysis	p. 223
11.4 Haplotype Reconstruction	p. 226
11.5 Linkage disequilibrium	p. 229
11.6 Quantitative Trait Locus (QTL) mapping in experimental crosses	p. 235
Acknowledgements	p. 240
References	p. 240
Section IV. Biological Sequence Analysis and Characterization	p. 247
Chapter 12 Predictive Functional Analysis of Polymorphisms: An Overview	p. 249
12.1 Introduction	p. 250
12.2 Principles of predictive functional analysis of polymorphisms	p. 252
12.3 The anatomy of promoter regions and regulatory elements	p. 257
12.4 The anatomy of genes	p. 258
12.5 Pseudogenes and regulatory mRNA	p. 264
12.6 Analysis of novel regulatory elements and motifs in nucleotide sequences	p. 264
12.7 Functional analysis on non-synonymous coding polymorphisms	p. 266
12.8 A note of caution on the prioritization of in silico predictions for further laboratory investigation	p. 268
12.9 Conclusions	p. 268
References	p. 269
Chapter 13 Functional In Silico Analysis of Non-coding SNPs	p. 273
13.1 Introduction	p. 273
13.2 General structure of chromatin-associated DNA	p. 275
13.3 General functions of regulatory regions	p. 276
13.4 Transcription Factor binding sites (TF-sites)	p. 276
13.5 Structural elements	p. 276
13.6 Organizational principles of regulatory regions	p. 277
13.7 RNA processing	p. 279
13.8 SNPs in regulatory regions	p. 279
13.9 Evaluation of non-coding SNPs	p. 280
13.10 SNPs and regulatory networks	p. 281
13.11 SNPs may affect the expression of a gene only in specific tissues	p. 281
13.12 In silico detection and evaluation of regulatory SNPs	p. 281
13.13 Getting promoter sequences	p. 282
13.14 Identification of relevant regulatory elements	p. 283
13.15 Estimation of functional consequences of regulatory SNPs	p. 284
13.16 Conclusion	p. 285
References	p. 285
Chapter 14 Amino Acid Properties and Consequences of Substitutions	p. 289
14.1 Introduction	p. 291
14.2 Protein features relevant to amino acid behaviour	p. 292
14.3 Amino acid classifications	p. 296
14.4 Properties of the amino acids	p. 298
14.5 Amino acid quick reference	p. 299
14.6 Studies of how mutations affect function	p. 311
14.7 A summary of the thought process	p. 313
References	p. 314
Section V. Genetics/Genomics Interfaces	p. 317
Chapter 15 Gene Expression Informatics and Analysis	p. 319
15.1 Introduction	p. 320
15.2 Technologies for the measurement of gene expression	p. 322
15.3 The Cancer Genome Anatomy Project (CGAP)	p. 324
15.4 Processing of SAGE data	p. 325
15.5 Integration of biological databases for the construction of the HTM	p. 334
15.6 The Human Transcriptome Map	p. 336
15.7 Regions of Increased Gene Expression (RIDGES)	p. 339
15.8 Discussion	p. 340
References	p. 341
Chapter 16 Proteomic Informatics	p. 345
16.1 Introduction	p. 346
16.2 Proteomic informatics	p. 347
16.3 Experimental workflow: classical proteomics	p. 347
16.4 Protein interaction networks	p. 351
16.5 Building protein interaction networks	p. 354
16.6 False negatives and false positives	p. 354
16.7 Analysing interaction networks	p. 355
16.8 Cell pathways	p. 356
16.9 Prediction of protein networks	p. 359
16.10 Assessment and validation of predictions	p. 363
16.11 Exploiting protein networks	p. 366
16.12 Deducing prediction rules from networks	p. 367
16.13 Conclusion	p. 368
Acknowledgements	p. 369
References	p. 369
Chapter 17 Concluding Remarks: Final Thoughts and Future Trends	p. 373
17.1 How many genes?	p. 374
17.2 Mapping the genome and gaining a view of the full depth of human variation	p. 375
17.3 Holistic analysis of complex traits	p. 376
17.4 A final word on bioinformatics	p. 376
Acknowledgements	p. 376
References	p. 376
Appendix I	p. 379
Appendix II	p. 381
Glossary	p. 387
Index	p. 391

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