Title:
Bioinformatics : genes, proteins and computers
Publication Information:
Oxford : BIOS Scientific Pub., 2003
ISBN:
9781859960547
Available:*
Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
---|---|---|---|---|---|
Searching... | 30000010042749 | QH323.5 B56 2003 | Open Access Book | Book | Searching... |
Searching... | 30000010179278 | QH323.5 B56 2003 | Open Access Book | Book | Searching... |
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Summary
Summary
Bioinformatics, the use of computers to address biological questions, has become an essential tool in biological research. It is one of the critical keys needed to unlock the information encoded in the flood of data generated by genome, protein structure, transcriptome and proteome research.
Bioinformatics: Genes, Proteins & Computers 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.
Table of Contents
Abbreviations | p. ix |
Contributors | p. xi |
Foreword | p. xiii |
1. 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 |
2. 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 |
3. 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 |
4. 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 |
5. 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 |
6. 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 |
7. 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 |
8. 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 |
9. 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 |
10. 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 |
11. 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 |
12. 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 |
13. 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 |
14. 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 |
15. 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 |
16. Proteomics | p. 245 |
The proteome | p. 245 |
Proteomics | p. 246 |
Technology platforms in proteomics | p. 246 |
Case studies | p. 254 |
Summary | p. 257 |
17. 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 |
18. 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 |