Evolutionary Computation in Bioinformatics by Elsevier Science & Technology (Hardback, 2002)
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About this product
- DescriptionBioinformatics has never been as popular as it is today. The gemics 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 t 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-kwn 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.
- Author BiographyGary 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. 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.
- PublisherElsevier Science & Technology
- Date of Publication27/09/2002
- SubjectComputing: Professional & Programming
- Series TitleThe Morgan Kaufmann Series in Artificial Intelligence
- Place of PublicationSan Francisco
- Country of PublicationUnited States
- ImprintMorgan Kaufmann Publishers In
- Content Noteillustrations
- Weight910 g
- Width187 mm
- Height235 mm
- Spine25 mm
- Edited byDavid W. Corne,Gary B. Fogel
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