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. I
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.
Researchers and graduate students in computer science and biology
- No. of pages:
- © Morgan Kaufmann 2003
- 16th September 2002
- Morgan Kaufmann
- eBook ISBN:
- Hardcover ISBN:
"This is a fine book that clearly discusses the applications of evolutionary computation techniques to a variety of different areas. It covers most topics a bioinformatician will find interesting." --Santosh Mishra, Eli Lilly
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.
Natural Selection, Inc.
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.
University of Reading