Bioinformatics, a field devoted to the interpretation and analysis of biological data using computational techniques, has evolved tremendously in recent years due to the explosive growth of biological information generated by the scientific community. Soft computing is a consortium of methodologies that work synergistically and provides, in one form or another, flexible information processing capabilities for handling real-life ambiguous situations. Several research articles dealing with the application of soft computing tools to bioinformatics have been published in the recent past; however, they are scattered in different journals, conference proceedings and technical reports, thus causing inconvenience to readers, students and researchers. This book, unique in its nature, is aimed at providing a treatise in a unified framework, with both theoretical and experimental results, describing the basic principles of soft computing and demonstrating the various ways in which they can be used for analyzing biological data in an efficient manner. Interesting research articles from eminent scientists around the world are brought together in a systematic way such that the reader will be able to understand the issues and challenges in this domain, the existing ways of tackling them, recent trends, and future directions. This book is the first of its kind to bring together two important research areas, soft computing and bioinformatics, in order to demonstrate how the tools and techniques in the former can be used for efficiently solving several problems in the latter.
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soft computing, evolutionary computation, genomic network, yeast sporulation, genomics experiments, mining data, genome informatics, memetic algorithm, active sites candidates, fibroblasts serum data, recurring substrings, protein surface motifs, cancer classification using microarray data, sporulation data, active site candidates, labeled dual graphs, molecular surface data, prediction strength threshold, cluster profile plots, real active sites, winner ant, using negative instances, residue contact maps, real gene expression data, truth functional value Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Nucleic Acids Research, Support Vector Machines, Inferring Regulations, Multiobjective Evolutionary Approach, Fuzzy Clustering of Microarray Data, Genetic Algorithms, Reconstructing Phylogenies, Journal of Molecular Biology, Filtering Protein Surface Motifs, Nature Genetics, Technical Report, Artificial Intelligence, Morgan Kaufmann, Computer Science, Artificial Life, Genome Research, Human Fibroblasts Serum, Academic Press, San Diego, Proceedings of National Academy of Science, Lecture Notes, Brain Cancer, John Wiley, Pearson Correlation Browse Sample Pages:
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soft computing, evolutionary computation, genomic network, yeast sporulation, genomics experiments, mining data, genome informatics, memetic algorithm, active sites candidates, fibroblasts serum data, recurring substrings, protein surface motifs, cancer classification using microarray data, sporulation data, active site candidates, labeled dual graphs, molecular surface data, prediction strength threshold, cluster profile plots, real active sites, winner ant, using negative instances, residue contact maps, real gene expression data, truth functional value Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Nucleic Acids Research, Support Vector Machines, Inferring Regulations, Multiobjective Evolutionary Approach, Fuzzy Clustering of Microarray Data, Genetic Algorithms, Reconstructing Phylogenies, Journal of Molecular Biology, Filtering Protein Surface Motifs, Nature Genetics, Technical Report, Artificial Intelligence, Morgan Kaufmann, Computer Science, Artificial Life, Genome Research, Human Fibroblasts Serum, Academic Press, San Diego, Proceedings of National Academy of Science, Lecture Notes, Brain Cancer, John Wiley, Pearson Correlation Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Surprise Me!
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