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Abstract Details
Activity Number:
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359
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Type:
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Contributed
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Date/Time:
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Tuesday, August 2, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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Abstract - #302133 |
Title:
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Biomarker Discovery in Lipidomics: A Systematic Comparison of Methods
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Author(s):
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Maiju Elisa Kujala*+
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Companies:
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University of Turku
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Address:
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Assistentinkatu 7, Turun yliopisto, International, 20014, Finland
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Keywords:
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Lipidomics ;
variable selection ;
biomarker detection
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Abstract:
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Lipidomic analyses, among other ''omics'' data sets, are becoming a popular part of pharmaceutical drug development. The goal of the present project is to develop statistical methodology for high dimensional and dependent data with real-life applications in lipidomics data sets keeping in mind that methods used should be acceptable both from scientific and regulatory points of view. The current research is a systematic comparison of methods used in biomarker discovery such as stepwise logistic regression, lasso logistic regression, and (regularized) discriminant analysis, among others. The ability of recover structures in these high dimensional data sets is studied by extensive simulations as well as illustrative examples. In addition, special issues such as missing values, sources of variation and respective normalizations and strong correlations between lipids are addresses.
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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