Evolutionary Computation in Bioinformatics (Hardcover)
暫譯: 生物資訊學中的進化計算 (精裝版)

This book offers a definitive resource that bridges two communities. Gary Fogel and David Corne, well-known representatives of these fields, have written an introduction to biology and bioinformatics for computer scientists and an introduction to evolutionary computation for biologists and for computer scientists unfamiliar with these techniques. The remaining eighteen chapters, written by leading computer scientists and biologists examine successful applications of evolutionary computation in areas such as: DNA sequencing, protein folding, DNA annotation, gene and protein classification, drug targeting, drug design, data mining of biological databases, and biodata visualisation. The appendix provides a full listing of biological data resources.

Contents

PART I - Introduction to the Concepts of Bioinformatics and Evolutionary Computation  
 
Chapter 1. An Introduction to Bioinformatics for Computer Scientists  
Chapter 2. An Introduction to Evolutionary Computation for Biologists  
 
PART II - Sequence and Structure Alignment  
Chapter 3. Determining Genome Sequences from Experimental Data Using Evolutionary Computation  
Chapter 4. Protein Structure Alignment Using Evolutionary Computation  
Chapter 5. Using Genetic Algorithms for Pairwise and Multiple Sequence Alignments  
 
PART III - Protein Folding  
Chapter 6. On the Evolutionary Search for Solutions to the Protein Folding Problem  
Chapter 7. Toward Effective Polypeptide Structure Prediction with Parallel Fast Messy Genetic Algorithms  
Chapter 8. Application of Evolutionary Computation to Protein Folding with Specialized Operators  

 
PART IV - Machine Learning and Inference  
Chapter 9. Identification of Coding Regions in DNA Sequences Using Evolved Neural Networks  
Chapter 10. Clustering Microarray Data with Evolutionary Algorithms  
Chapter 11. Evolutionary Computation and Fractal Visualization of Sequence Data  
Chapter 12. Identifying Metabolic Pathways and Gene Regulation Networks with Evolutionary Algorithms  
Chapter 13. Evolutionary Computational Support for the Characterization of Biological Systems  

PART V - Feature Selection  
Chapter 14. Discovery of Genetic and Environmental Interactions in Disease Data Using Evolutionary Computation  
Chapter 15. Feature Selection Methods Based on Genetic Algorithms for in Silico Drug Design  
Chapter 16. Interpreting Analytical Spectra with Evolutionary Computation  
Appendix: Internet Resources for Bioinformatics Data and Tools