Computational Intelligence in Bioinformatics: 7 (IEEE Press Series on Computational Intelligence) - Tapa dura

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Gary B. Fogel, PhD, is Vice President of Natural Selection, Inc., and his current research interests focus on the application of computational intelligence methods to problems in the biomedical sciences. He is a senior member of the IEEE and serves as an Associate Editor on three IEEE journals.

David W. Corne holds a Chair in Computer Science at Heriot-Watt University, Edinburgh, Scotland, and his research interests include evolutionary computation, multi-objective optimization, bioinformatics, telecommunications, and general aspects and applications of nature-inspired computation.

Yi Pan, PhD, is Chair and Professor of Computer Science at Georgia State University and his research interests include high-performance computing, networking, and bioinformatics. Dr. Pan has coedited over twenty books and his recent research has been supported by the NSF, NIH, NSFC, AFOSR, AFRL, JSPS, IISF, and the states of Georgia and Ohio.

De la contraportada

Learn how to apply computational intelligence methods to solve problems in bioinformatics

Combining biology, computer science, mathematics, and statistics, the field of bioinformatics has become a hot new discipline with profound impacts on all aspects of biology and industrial application. However, due to limitations of traditional algorithms, scientists have been increasingly forced to rethink the way they adapt modeling approaches to challenges created by a wealth of biological data. Now, as computational intelligence (CI) has been applied to bioinformatics with promising results, there is a need for a thorough and comprehensive overview of the importance of and recent developments in CI methods across a range of bioinformatics problems. Computational Intelligence in Bioinformatics offers an introduction to the topic, covering the most relevant and popular CI methods, while also encouraging the implementation of these methods to readers' research.

Organized in self-contained chapters developed and edited by leading educators in their fields, Computational Intelligence in Bioinformatics explains and applies CI methods to problem areas, such as:

• Gene expression analysis and systems biology

• Sequence analysis and feature detection

• Molecular structure and phylogenetics

• Medicine

Enhanced by an accompanying Web site (www.ci-in-bioinformatics.com) that includes data sets used in the book, software that can be obtained for open distribution, a selection of the best and easiest-to-use software for the CI techniques covered in the book, and "Challenge Problems" whose progress will be reported and tracked on the site, Computational Intelligence in Bioinformatics serves as a valuable resource for professionals who are interested in applying CI to solve problems in bioinformatics applications, and also accommodates the needs of graduate-level students in bioinformatics courses.

De la solapa interior

Learn how to apply computational intelligence methods to solve problems in bioinformatics

Combining biology, computer science, mathematics, and statistics, the field of bioinformatics has become a hot new discipline with profound impacts on all aspects of biology and industrial application. However, due to limitations of traditional algorithms, scientists have been increasingly forced to rethink the way they adapt modeling approaches to challenges created by a wealth of biological data. Now, as computational intelligence (CI) has been applied to bioinformatics with promising results, there is a need for a thorough and comprehensive overview of the importance of and recent developments in CI methods across a range of bioinformatics problems. Computational Intelligence in Bioinformatics offers an introduction to the topic, covering the most relevant and popular CI methods, while also encouraging the implementation of these methods to readers' research.

Organized in self-contained chapters developed and edited by leading educators in their fields, Computational Intelligence in Bioinformatics explains and applies CI methods to problem areas, such as:

• Gene expression analysis and systems biology

• Sequence analysis and feature detection

• Molecular structure and phylogenetics

• Medicine

Enhanced by an accompanying Web site (www.ci-in-bioinformatics.com) that includes data sets used in the book, software that can be obtained for open distribution, a selection of the best and easiest-to-use software for the CI techniques covered in the book, and Challenge Problems whose progress will be reported and tracked on the site, Computational Intelligence in Bioinformatics serves as a valuable resource for professionals who are interested in applying CI to solve problems in bioinformatics applications, and also accommodates the needs of graduate-level students in bioinformatics courses.