Bioinformatics Using Computational Intelligence Paradigms

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Udo Seiffert, Patrick Schweizer
Springer Science & Business Media, Jan 17, 2005 - Computers - 211 pages
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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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Contents

Detecting Molecular Diseases with CaseBased Reasoning
1
Prototype Based Recognition of Splice Sites
25
Content Based Image Compression in Biomedical HighThroughput Screening Using Artificial Neural Networks
57
Discriminative Clustering of Yeast Stress Response
75
A Dynamic Model of Gene Regulatory Networks Based on Inertia Principle
93
Class Prediction with Microarray Datasets
119
Random Voronoi Ensembles for Gene Selection in DNA Microarray Data
143
Cancer Classification with Microarray Data Using Support Vector Machines
167
Artificial Neural Networks for Reducing the Dimensionality of Gene Expression Data
191
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Page 211 - LM (2002). The use of molecular profiling to predict survival after chemotherapy for diffuse large-B-cell lymphoma. N Engl J Med 346: 1937-1947.
Page 211 - Rosenwald A, Alizadeh AA, Widhopf G, Simon R, Davis RE, Yu X, Yang L, Pickeral OK, Rassenti LZ, Powell J, Botstein D, Byrd JC, Grever MR, Cheson BD, Chiorazzi N, Wilson WH, Kipps TJ, Brown PO, Staudt LM.
Page 211 - Wiestner A, Rosenwald A, Barry TS, et al. ZAP-70 expression identifies a chronic lymphocytic leukemia subtype with unmutated immunoglobulin genes, inferior clinical outcome, and distinct gene expression profile. Blood 2003; 101:4944-51.