This book is an excellent introductory text describing the use of bioinformatics to analyze genomic and post-genomic data. It has been translated from the original popular French edition, which was based on a course taught at the well-respected ?cole Polytechnique in Palaiseau. This edition has been fully revised and updated by the authors.After a brief introduction to gene structure and sequence determination, it describes the techniques used to identify genes, their protein-coding sequences and regulatory regions. The book discusses the methodology of comparative genomics, using information from different organisms to deduce information about unknown sequences. There is a comprehensive chapter on structure prediction, covering both RNA and protein. Finally, the book describes the complex networks of RNA and protein that exist within the cell and their interactions, ending with a discussion of the simulation approaches that can be used to model these networks.Praise from the reviews:“In context of the new developments the genomic era has brought, Bioinformatics: Genomics and Post-Genomics becomes a fundamental and indispensable resource for undergraduate and early graduate students…insightfully authored…will immensely help students…in establishing important foundations while shaping their careers.” NEWSLETTER, BRITISH SOCIETY OF CELL BIOLOGY
Author(s): Frederic Dardel, Francois Kepes
Edition: 1
Year: 2006
Language: English
Pages: 252
Cover......Page 2
Contents......Page 8
Preface to the French edition......Page 10
Preface to the English edition......Page 12
1.1 Automatic sequencing......Page 14
1.2 Sequencing strategies......Page 17
1.3 Fragmentation strategies......Page 21
1.4 Sequence assembly......Page 25
1.5 Filling gaps......Page 27
1.6 Obstacles to reconstruction......Page 29
1.7 Utilizing a complementary ‘large’1 clone library......Page 31
1.8 The first large-scale sequencing project: The Haemophilus influenzae genome......Page 32
1.9 cDNA and EST......Page 33
2.1 Introduction: Comparison as a sequence prediction method......Page 38
2.2 A sample molecule: the human androsterone receptor......Page 39
2.3 Sequence homologies – functional homologies......Page 40
2.4 Comparison matrices......Page 41
2.5 The problem of insertions and deletions......Page 46
2.6 Optimal alignment: the dynamic programming method......Page 47
2.7 Fast heuristic methods......Page 51
2.8 Sensitivity, specificity, and confidence level......Page 59
2.9 Multiple alignments......Page 63
3.1 General properties of genomes......Page 74
3.2 Genome comparisons......Page 80
3.3 Gene evolution and phylogeny: applications to annotation......Page 88
4.2 Genes and the genetic code......Page 98
4.3 Expression signals......Page 100
4.5 Sites located on DNA......Page 104
4.7 Pattern detection methods......Page 109
5.2 Nucleotide base and amino acid distribution......Page 120
5.3 The biological basis of codon bias......Page 125
5.4 Using statistical bias for prediction......Page 126
5.5 Modeling DNA sequences......Page 129
5.6 Complex models......Page 133
5.7 Sequencing errors and hidden Markov models......Page 136
5.9 The search for genes – a difficult art......Page 140
6.1 The structure of RNA......Page 144
6.2 Properties of the RNA molecule......Page 145
6.3 Secondary RNA structures......Page 147
6.4 Thermodynamic stability of RNA structures......Page 151
6.5 Finding the most stable structure......Page 157
6.6 Validation of predicted secondary structures......Page 162
6.7 Using chemical and enzymatic probing to analyze folding......Page 163
6.8 Long-distance interactions and three-dimensional structure prediction......Page 165
6.9 Protein structure......Page 168
6.10 Secondary structure prediction......Page 171
6.11 Three-dimensional modeling based on homologous protein structure......Page 174
6.12 Predicting folding......Page 179
7.1 Introduction......Page 182
7.2 Post-genomic methods......Page 183
7.3 Macromolecular networks......Page 195
7.4 Topology of macromolecular networks......Page 206
7.5 Modularity and dynamics of macromolecular networks......Page 212
7.6 Inference of regulatory networks......Page 219
8: Simulation of biological processes in the genome context......Page 224
8.2 Prediction and explanation......Page 226
8.3 Simulation of molecular networks......Page 228
8.4 Generic post-genomic simulators......Page 239
Index......Page 246
