Evolutionary Computation in Bioinformatics 1st Edition by Gary Fogel, David Corne 0511226071 9780511226076

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Product details:

ISBN 10: 0511226071 

ISBN 13: 9780511226076

Author: Gary B. Fogel, David W. Corne

Bioinformatics has never been as popular as it is today. The genomics revolution is generating so much data in such rapid succession that it has become difficult for biologists to decipher. In particular, there are many problems in biology that are too large to solve with standard methods. Researchers in evolutionary computation (EC) have turned their attention to these problems. They understand the power of EC to rapidly search very large and complex spaces and return reasonable solutions. While these researchers are increasingly interested in problems from the biological sciences, EC and its problem-solving capabilities are generally not yet understood or applied in the biology community.This book offers a definitive resource to bridge the computer science and biology communities. Gary Fogel and David Corne, well-known representatives of these fields, introduce biology and bioinformatics to computer scientists, and evolutionary computation to biologists and computer scientists unfamiliar with these techniques. The fourteen chapters that follow are written by leading computer scientists and biologists who examine successful applications of evolutionary computation to various problems in the biological sciences.

* Describes applications of EC to bioinformatics in a wide variety of areas including DNA sequencing, protein folding, gene and protein classification, drug targeting, drug design, data mining of biological databases, and biodata visualization.
* Offers industrial and academic researchers in computer science, biology, and bioinformatics an important resource for applying evolutionary computation.
* Includes a detailed appendix of biological data resources.

Table of 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

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