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基本説明
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.
Full Description
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.
Contents
PART I - Introduction to the Concepts of Bioinformatics and Evolutionary Computation
Chapter 1. An Introduction to Bioinformatics for Computer Scientists
By David W. Corne and Gary B. Fogel
Chapter 2. An Introduction to Evolutionary Computation for Biologists
By Gary B. Fogel and David W. Corne
PART II - Sequence and Structure Alignment
Chapter 3. Determining Genome Sequences from Experimental Data Using Evolutionary Computation
By Jacek Blazewic and Marta Kasprzak
Chapter 4. Protein Structure Alignment Using Evolutionary Computation
By Joseph D. Szustakowski and Zhipeng Weng
Chapter 5. Using Genetic Algorithms for Pairwise and Multiple Sequence Alignments
By Cédric Notredame
PART III - Protein Folding
Chapter 6. On the Evolutionary Search for Solutions to the Protein Folding Problem
By Garrison W. Greenwood and Jae-Min Shin
Chapter 7. Toward Effective Polypeptide Structure Prediction with Parallel Fast Messy Genetic Algorithms
By Gary B. Lamont and Laurence D. Merkle
Chapter 8. Application of Evolutionary Computation to Protein Folding with Specialized Operators
By Steffen Schulze-Kremer
PART IV - Machine Learning and Inference
Chapter 9. Identification of Coding Regions in DNA Sequences Using Evolved Neural Networks
By Gary B. Fogel, Kumar Chellapilla, and David B. Fogel
Chapter 10. Clustering Microarray Data with Evolutionary Algorithms
By Emanuel Falkenauer and Arnaud Marchand
Chapter 11. Evolutionary Computation and Fractal Visualization of Sequence Data
By Dan Ashlock and Jim Golden
Chapter 12. Identifying Metabolic Pathways and Gene Regulation Networks with Evolutionary Algorithms
By Junji Kitagawa and Hitoshi Iba
Chapter 13. Evolutionary Computational Support for the Characterization of Biological Systems
By Bogdan Filipic and Janez Strancar
PART V - Feature Selection
Chapter 14. Discovery of Genetic and Environmental Interactions in Disease Data Using Evolutionary Computation
By Laetitia Jourdan, Clarisse Dhaenens[AQ2], and El-Ghazali Talbi
Chapter 15. Feature Selection Methods Based on Genetic Algorithms for in Silico Drug Design
By Mark J. Embrechts, Muhsin Ozdemir, Larry Lockwood, Curt Breneman, Kristin Bennet, Dirk Devogelaere, and Marcel Rijkaert
Chapter 16. Interpreting Analytical Spectra with Evolutionary Computation
By Jem J. Rowland
Appendix: Internet Resources for Bioinformatics Data and Tools
