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Activity Number:
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260
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 5, 2008 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Nonparametric Statistics
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| Abstract - #301468 |
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Title:
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Dimension Reduction with Possible Application in Bioinformatics
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Author(s):
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Wenxuan Zhong*+
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Companies:
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University of Illinois at Urbana-Champaign
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Address:
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119 Illini Hall, Champaign, IL, 61822,
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Keywords:
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Correlation Pursuit ; Motif Finding ; Variable Selection ; Dimension Reduction
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Abstract:
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Information for regulating a gene's transcription is contained in the conserved patterns (motifs) on the upstream/downstream DNA sequence (promoter region) close to the target gene. By combining the information contained in both gene expression measurements and genes' promoter sequences, I proposed a novel procedure for identifying functional active motifs under certain stimuli. A dimensional reduction model was used to associate promoter sequence information of a gene and its mRNA expression measurements. A correlation pursuit (corps) variable selection method was developed to select the potential functional active promoter sequences. In this talk, I will demonstrate the advantage of the corps both theoretically and empirically.
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