Bioinformatics and computational intelligence are undoubtedly remarkably fast growing fields of research and real-world applications with enormous potential for current and future developments. Bioinformatics Using Computational Intelligence Paradigms contains recent theoretical approaches and guiding applications of biologically inspired information processing systems (computational intelligence) against the background of bioinformatics. This carefully edited monograph combines the latest results of bioinformatics and computational intelligence, and offers promising cross-fertilization and interdisciplinary work between these growing fields.
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Bioinformatics as well as Computational Intelligence are undoubtedly remarkably fast growing fields of research and real-world applications with enormous potential for current and future developments. "Bioinformatics using Computational Intelligence Paradigms" contains recent theoretical approaches and guiding applications of biologically inspired information processing systems(Computational Intelligence) against the background of bioinformatics. This carefully edited monograph combines the latest results of Bioinformatics and Computational Intelligence and offers a promising cross-fertilisation and interdisciplinary work between these growing fields.
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weighted genes, absolute call values, saliency vectors, hypothesis margin, margin between the two classes, lymphoma data, microarray datasets, shrunken centroids, gene reduction, leukemia data, inertial model, splice site recognition, myeloma cases, mutant strain lacking, gene expression data, top genes, complete cds, gene regulatory networks, closest prototype, current problem situation, training round, virtual cell, simulated profiles, repair network, learning vector quantization Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Samuel Kaski, Neural Computation, Day Mbtw, Number of Genes Fig, Cambridge University Press, International Conference, Journal of Computational Biology, Multiple-Layer Perceptrons, Nucleid Acid Research, High Throughput Screening, Rank Gene, Springer Verlag, University of California New!
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weighted genes, absolute call values, saliency vectors, hypothesis margin, margin between the two classes, lymphoma data, microarray datasets, shrunken centroids, gene reduction, leukemia data, inertial model, splice site recognition, myeloma cases, mutant strain lacking, gene expression data, top genes, complete cds, gene regulatory networks, closest prototype, current problem situation, training round, virtual cell, simulated profiles, repair network, learning vector quantization Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Samuel Kaski, Neural Computation, Day Mbtw, Number of Genes Fig, Cambridge University Press, International Conference, Journal of Computational Biology, Multiple-Layer Perceptrons, Nucleid Acid Research, High Throughput Screening, Rank Gene, Springer Verlag, University of California New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Back Cover | Surprise Me!
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This book cites 42
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- Statistical Learning Theory by Vladimir N. Vapnik on page 117, page 141, and page 164
- Self-Organizing Maps by Teuvo Kohonen on page 4 (1), and page 4 (2)
- Evolutionary Computation in Data Mining (Studies in Fuzziness and Soft Computing) by Ashish Ghosh in Front Matter
- Intelligent Multimedia Processing with Soft Computing (Studies in Fuzziness and Soft Computing) by Yap Peng Tan in Front Matter
- Simulating Fuzzy Systems (Studies in Fuzziness and Soft Computing) by James J. Buckley in Front Matter
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- Intelligent Paradigms for Healthcare Enterprises: Systems Thinking (Studies in Fuzziness and Soft Computing) by Barry G. Silverman in Front Matter
- Foundations and Advances in Data Mining (Studies in Fuzziness and Soft Computing) by Wesley Chu in Front Matter
- Fuzzy Group Theory (Studies in Fuzziness and Soft Computing) by John N. Mordeson in Front Matter
- Extending the Scalability of Linkage Learning Genetic Algorithms: Theory & Practice (Studies in Fuzziness and Soft Computing) by Ying-ping Chen in Front Matter
- Rule-Based Evolutionary Online Learning Systems: A Principled Approach to LCS Analysis and Design (Studies in Fuzziness and Soft Computing) by Martin V. Butz in Front Matter
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