"Computational Intelligence (CI) is a successor of artificial intelligence combining elements of learning, adaptation, evolution and logic to create programs that are, in some sense, intelligent. CI exhibits an ability to learn or deal with new situations, such that the system is perceived to possess one or more attributes of reason. The different methodologies in CI work synergistically and provide, in one form or another, flexible information processing capabilities for handling a huge volume of real life data with noises, ambiguity, and missing values. Solving problems often involves search for useful regularities or patterns in large amounts of data. A typical characteristic of biological data is high dimensionality with low sample size. This poses grand challenges to traditional pattern analysis techniques, necessitating the development of sophisticated approaches--Provided by publisher.
In the field of biological informatics, new methods of data collection that gather huge amounts of data and produce new data types have spurred advanced methods of searching for useful regularities or patterns in these data sets. Of these methods, computational intelligence has found particular favor among researchers. This book synthesizes current research in the integration of computational intelligence and pattern analysis techniques.
Computational Intelligence and Pattern Analysis in Biological Informatics brings together research articles by active practitioners, reporting recent advances in integrating computational intelligence and pattern analysis techniques for analyzing biological data in order to extract more meaningful information and insights from them. It covers highly relevant topics, including rational drug design and the involvement of microRNAs in human diseases.
Packed with theoretical and experimental results, Computational Intelligence and Pattern Analysis in Biological Informatics deepens the understanding of the ways in which the basic principles of computational intelligence and pattern analysis can be used for analyzing biological data in an efficient manner. Graduate students and researchers in computer science, bioinformatics, computational and molecular biology, biochemistry, systems science, and information technology will find this unique volume a valuable tool.
An invaluable tool in Bioinformatics, this unique volume provides both theoretical and experimental results, and describes basic principles of computational intelligence and pattern analysis while deepening the reader's understanding of the ways in which these principles can be used for analyzing biological data in an efficient manner.
This book synthesizes current research in the integration of computational intelligence and pattern analysis techniques, either individually or in a hybridized manner. The purpose is to analyze biological data and enable extraction of more meaningful information and insight from it. Biological data for analysis include sequence data, secondary and tertiary structure data, and microarray data. These data types are complex and advanced methods are required, including the use of domain-specific knowledge for reducing search space, dealing with uncertainty, partial truth and imprecision, efficient linear and/or sub-linear scalability, incremental approaches to knowledge discovery, and increased level and intelligence of interactivity with human experts and decision makers
- Chapters authored by leading researchers in CI in biology informatics.
- Covers highly relevant topics: rational drug design; analysis of microRNAs and their involvement in human diseases.
- Supplementary material included: program code and relevant data sets correspond to chapters.
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