Evolutionary computation in bioinformatics - Fogel, Gary, 1968-; Corne, David (Amsterdam ; Boston : Morgan Kaufmann Publishers, 2003)
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.
An introduction to bioinformatics for computer scientists / David W. Corne and Gary B. Fogel -- An introduction to evolutionary computation for biologists / Gary B. Fogel and David W. Corne -- Determining genome sequences from experimental data using evolutionary computation / Jacek Blazewicz and Marta Kasprzak -- Protein structure alignment using evolutionary computation / Joseph D. Szustakowski and Zhiping Weng -- Using genetic algorithms for pairwise and multiple sequence alignments / Cβedric Notredame -- On the evolutionary search for solutions to the protein folding problem / Garrison W. Greenwood and Jae-Min Shin -- Toward effective polypeptide structure prediction with parallel fast messy genetic algorithms / Gary B. Lamont and Laurence D. Merkle -- Application of evolutionary computation to protein folding with specialized operators / Steffen Schulze-Kremer -- Identification of coding regions in DNA sequences using evolved neural networks / Gary B. Fogel, Kumar Chellapilla and David B. Fogel -- Clustering microarray data with evolutionary algorithms / Emanuel Falkenauer and Arnaud Marchand -- Evolutionary computation and fractal visualization of sequence data / Dan Ashlock and Jim Golden -- Identifying metabolic pathways and gene regulation networks with evolutionary algorithms / Junji Kitagawa and Hitoshi Iba --Evolutionary computational support for the characterization of biological systems / Bogdan Filipiιc and Janez ιStrancar -- Discovery of genetic and environmental interactions in disease data using evolutionary computation / Laetitia Jourdan, Clarisse Dhaenens-Flipo and El-Ghazali Talbi -- Feature selection methods based on genetic algorithms for in silico drug design / Mark J. Embrechts, Muhsin Ozdemir, Larry Lockwood, Curt Breneman, Kristin Bennett, Dirk Devogelaere and Marcel Rijckaert --Interpreting analytical spectra with evolutionary computation / Jem J. Rowland.
Includes bibliographical references.
Keywords: Bioinformatics; Evolutionary computation; Electronic books