Discovering informative genes from gene expression data : a multi-strategy approach

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TypeArticle
ConferenceThe 18th European Conference on Machine Learning, September 17-21, 2007, Warsaw, Poland
Subjectgene expression data analysis; multi-strategy learning; data mining and knowledge discovery
AbstractThis paper discusses the issue of dealing with large volume of high throughput genomics data and applying unsupervised multi-strategy methods to identify differentially expressed genes. We introduce a novel method that consists of 8 steps. The approach is applied to a set of genomics data obtained from a cancer research study. We demonstrate the effectiveness of our method which includes some validation using biological experiments and literature search.
Publication date
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada; NRC Biotechnology Research Institute
Peer reviewedNo
NRC number49839
NPARC number5765693
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Record identifier201ab8c6-53af-49cc-9143-9fc3df1b076d
Record created2009-03-29
Record modified2016-05-09
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