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Evolutionary Data Mining for Genomics
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Author(s): Laetitia Jourdan (LIFL, University of Lille 1, France), Clarisse Dhaenens (LIFL, University of Lille 1, France)and El-Ghazali Talbi (LIFL, University of Lille 1, France)
Copyright: 2005
Pages: 5
Source title:
Encyclopedia of Data Warehousing and Mining
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-59140-557-3.ch091
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Abstract
Knowledge discovery from genomic data has become an important research area for biologists. Nowadays, a lot of data is available on the Web, but it is wrong to say that corresponding knowledge is also available. For example, the first draft of the human genome, which contains 3,000,000,000 letters, was achieved in June 2000, but, up to now, only a small part of the hidden knowledge has been discovered. This is the aim of bioinformatics, which brings together biology, computer science, mathematics, statistics, and information theory to analyze biological data for interpretation and prediction. Hence, many problems encountered while studying genomic data may be modeled as data mining tasks, such as feature selection, classification, clustering, or association rule discovery.
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