Bioinformatics: Genes, Proteins and Computers

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ISBN: 9781859960547 | 1859960545
Cover: Nonspecific Binding
Copyright: 7/29/2003

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The Advanced Text series is designed for students taking advanced-level courses, including upper-level undergraduates and graduate students. Titles in this series will also be invaluable to researchers new to a field, and to established researchers as a basic reference text. Bioinformatics covers both the more traditional approaches to bioinformatics, including gene and protein sequence analysis and structure prediction, and more recent technologies such as datamining of transcriptomic and proteomic data to provide insights on cellular mechanisms and the causes of disease.

Abbreviations	p. ix
Contributors	p. xi
Foreword	p. xiii
Molecular evolution	p. 1
Molecular evolution is a fundamental part of bioinformatics	p. 1
Evolution of protein families	p. 9
Outlook: Evolution takes place at all levels of biological organization	p. 15
Gene finding	p. 19
Concepts	p. 19
Finding genes in bacterial genomes	p. 20
Finding genes in higher eukaryotes	p. 21
Detecting non-coding RNA genes	p. 27
Sequence comparison methods	p. 29
Concepts	p. 29
Data resources	p. 30
Algorithms for pairwise sequence comparison	p. 32
Fast database search methods	p. 38
Assessing the statistical significance of sequence similarity	p. 42
Intermediate sequence searching	p. 44
Validation of sequence alignment methods by structural data	p. 44
Multiple sequence alignment	p. 45
Amino acid residue conservation	p. 49
Concepts	p. 49
Models of molecular evolution	p. 49
Substitution matrices	p. 50
Scoring residue conservation	p. 57
Methods for scoring conservation	p. 59
Insights and conclusions	p. 64
Function prediction from protein sequence	p. 65
Overview	p. 65
The similar sequence-similar structure-similar function paradigm	p. 65
Functional annotation of biological sequences	p. 66
Outlook: context-dependence of protein function	p. 77
Protein structure comparison	p. 81
Concepts	p. 81
Data resources	p. 84
Algorithms	p. 84
Statistical methods for assessing structural similarity	p. 99
Multiple structure comparison and 3-D templates for structural families	p. 100
Conclusions	p. 101
Protein structure classifications	p. 103
Concepts	p. 103
Data resources	p. 104
Protocols used in classifying structures	p. 104
Descriptions of the structural classification hierarchy	p. 111
Overview of the populations in the different structural classifications and insights provided by the classifications	p. 118
Comparative modeling	p. 121
Concepts	p. 121
Why do comparative modeling?	p. 121
Experimental methods	p. 123
Evaluation of model quality	p. 131
Factors influencing model quality	p. 132
Insights and conclusions	p. 133
Protein structure prediction	p. 135
Concepts	p. 135
Strategies for protein structure prediction	p. 135
Secondary structure prediction	p. 138
Fold recognition methods	p. 145
Ab initio prediction methods	p. 149
Critically assessing protein structure prediction	p. 149
Conclusions	p. 150
From protein structure to function	p. 151
Introduction	p. 151
What is function?	p. 152
Challenges of inferring function from structure	p. 152
Methods of functional evolution	p. 152
Functional classifications	p. 154
From structure to function	p. 156
Evolution of protein function from a structural perspective	p. 164
Structural genomics	p. 171
Conclusions	p. 174
From structure-based genome annotation to understanding genes and proteins	p. 175
Concepts	p. 175
Computational structural genomics: structural assignment of genome sequences	p. 175
Methods and data resources for computational structural genomics	p. 176
Proteome and protein evolution by computational structural genomics	p. 181
Evolution of enzymes and metabolic pathways by structural annotation of genomes	p. 186
Summary and outlook	p. 191
Global approaches for studying protein-protein interactions	p. 193
Concepts	p. 193
Protein-protein interactions	p. 193
Experimental approaches for large-scale determination of protein-protein interactions	p. 195
Structural analyses of domain interactions	p. 196
The use of gene order to predict protein-protein interactions	p. 198
The use of phylogeny to predict protein-protein interactions	p. 200
Summary and outlook	p. 200
Predicting the structure of protein-biomolecular interactions	p. 203
Concepts	p. 203
Why predict molecular interactions?	p. 203
Practical considerations	p. 204
Molecular complementarity	p. 204
The search problem	p. 209
Conformational flexibility	p. 211
Evaluation of models	p. 214
Visualization methods	p. 215
Experimental use of DNA arrays	p. 217
Concepts	p. 217
Methods for large-scale analysis of gene expression	p. 218
Using microarrays	p. 219
Properties and processing of array data	p. 221
Data normalization	p. 223
Microarray standards and databases	p. 226
Mining gene expression data	p. 229
Concepts	p. 229
Data mining methods for gene expression analysis	p. 230
Clustering	p. 231
Classification	p. 241
Conclusion and future research	p. 244
Proteomics	p. 245
The proteome	p. 245
Proteomics	p. 246
Technology platforms in proteomics	p. 246
Case studies	p. 254
Summary	p. 257
Data managament of biological information	p. 259
Concepts	p. 259
Data management concepts	p. 260
Data management techniques	p. 263
Challenges arising from biological data	p. 270
Conclusions	p. 271
Internet technologies for bioinformatics	p. 273
Concepts	p. 273
Methods and standards	p. 274
Insights and conclusions	p. 281
Glossary	p. 283
Index	p. 293
Table of Contents provided by Rittenhouse. All Rights Reserved.

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Bioinformatics: Genes, Proteins and Computers

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