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An environment for knowledge discovery in biology

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This paper describes a data mining environment for knowledge discovery in bioinformatics applications. The system has a generic kernel that implements the mining functions to be applied to input primary databases, with a warehouse architecture, of biomedical information. Both supervised and unsupervised classification can be implemented within the kernel and applied to data extracted from the primary database, with the results being suitably stored in a complex object database for knowledge discovery. The kernel also includes a specific high-performance library that allows designing and applying the mining functions in parallel machines. The experimental results obtained by the application of the kernel functions are reported. © 2003 Elsevier Ltd. All rights reserved.

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Bioinformatics, Databases, Gene expression, High-performance computing, Knowledge discovery, Microarrays, Pattern recognition, knowledge discovery, Warehouse architectures, Biomedical engineering, Computer architecture, Database systems, Knowledge acquisition, Data mining, analytic method, bioinformatics, biology, computer analysis, data analysis, data base, gene expression, human, human tissue, information processing device, machine, medical information, medical research, mining, pattern recognition, priority journal, science, technique, Computational Biology, Gene Expression Profiling, Knowledge, Systems Integration

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Inglês

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Computers in Biology and Medicine, v. 34, n. 5, p. 427-447, 2004.

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