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|a Bioinformatics Using Computational Intelligence Paradigms
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|c edited by Udo Seiffert, Patric Schweizer.
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|a 1st ed. 2005.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2005.
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|a VII, 211 p.
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|a Studies in Fuzziness and Soft Computing,
|x 1434-9922 ;
|v 176
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|a Springer eBook Collection
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|a Medical Bioinformatics: Detecting Molecular Diseases with Case-Based Reasoning -- Prototype Based Recognition of Splice Sites -- Contact Based Image Compression in Biomedical High-Throughput Screening Using Artificial Neural Networks -- Discriminative Clustering of Yeast Stress Response -- A Dynamic Model of Gene Regulatory Networks Based on Inertia Principle -- Class Prediction with Microarray Datasets -- Random Voronoi Ensembles for Gene Selection in DNA Microarray Data -- Cancer Classification with Microarray Data Using Support Vector Machines -- Artificial Neural Networks for Reducing the Dimensionality of Gene Expression Data.
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| 520 |
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|a 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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|a Loaded electronically.
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|a Electronic access restricted to members of the Holy Cross Community.
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|a Computers.
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|a Computational intelligence.
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| 650 |
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|a Applied mathematics.
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| 650 |
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|a Engineering mathematics.
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| 650 |
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|a Bioinformatics.
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| 650 |
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|a Artificial intelligence.
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|a Biotechnology.
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| 690 |
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