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Evolutionary Computation in Bioinformatics
- 1st Edition - September 16, 2002
- Editors: Gary B. Fogel, David W. Corne
- Language: English
- Hardback ISBN:9 7 8 - 1 - 5 5 8 6 0 - 7 9 7 - 2
- eBook ISBN:9 7 8 - 0 - 0 8 - 0 5 0 6 0 8 - 1
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… Read more
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Request a sales quoteBioinformatics 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.
* 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.
Researchers and graduate students in computer science and biology
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
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
- No. of pages: 393
- Language: English
- Edition: 1
- Published: September 16, 2002
- Imprint: Morgan Kaufmann
- Hardback ISBN: 9781558607972
- eBook ISBN: 9780080506081
GF
Gary B. Fogel
Gary B. Fogel is a senior staff scientist at Natural Selection, Inc., in La Jolla, California.His research interests include the application of evolutionary computationto problems in the biomedical sciences and evolutionary biology. He received aB.A. in biology from the University of California, Santa Cruz, in 1991 and a Ph.D.in biology from the University of California, Los Angeles, in 1998 with a focus onevolutionary biology. While at UCLA, Dr. Fogel was a fellow of the Center for theStudy of Evolution and the Origin of Life and earned several teaching and researchawards. He is a current member of the International Society for the Studyof the Origin of Life, the Society for the Study of Evolution, IEEE, Sigma Xi, andthe Evolutionary Programming Society. He currently serves as an associate editorfor IEEE Transactions on Evolutionary Computation and BioSystems and was a technicalco-chair for the recent 2000 Congress on Evolutionary Computation. He is alsoa senior staff scientist at the Center for Excellence in Evolutionary Computation,a nonprofit organization that promotes scientific research and development ofevolutionary algorithms.
Affiliations and expertise
Natural Selection, Inc.DC
David W. Corne
David W. Corne is a reader in evolutionary computation (EC) at the University of Reading. His early research on evolutionary timetabling (with Peter Ross) resultedin the first freely available and successful EC-based general timetabling programfor educational and other institutions. His later EC work has been in suchareas as DNA pattern mining, promoter modeling, phylogeny, scheduling, layoutdesign, telecommunications, data mining, algorithm comparison issues, and multiobjectiveoptimization. Recent funded work (with Douglas Kell) applies EC directlyto the in vivo optimization of proteins. He is an associate editor of the IEEETransactions on Evolutionary Computation and a founding co-editor of the Journal ofScheduling. Dr. Corne is on the editorial boards of Applied Soft Computing and the InternationalJournal of Systems Science, and he serves on a host of international conferenceprogram committees. Other recent edited books include New Ideas in Optimization(with Marco Dorigo and Fred Glover), Telecommunications Optimization: Heuristic andAdaptive Techniques (with Martin Oates and George Smith), and Creative EvolutionarySystems (with Peter Bentley). He is also a director of Evosolve (United Kingdomregistered charity number 1086384, with Jeanne Lynch-Aird, Paul Marrow, GlenysOates, and Martin Oates), a nonprofit organization that promotes the use of advancedcomputation technologies to enhance the quality of life.
Affiliations and expertise
University of ReadingRead Evolutionary Computation in Bioinformatics on ScienceDirect