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- W2361920909 abstract "The metabolomics dataset is disturbed by various stimuli inevitably.The main task for metabolo mics data preprocessing is to reduce the impacts of the disturbing factors.In present work,the formation of data variance and their distribution in feature space are analyzed.Furthermore,a new method to filtrate unknown disturb ing factors is proposed and the significance of interesting factors is improved.The efficiency of the new filtering al gorithm is estimated by real metabolomics dataset.Comparing with orthogonal signal correction(OSC) method,the experiment shows that the new method is superior in reducing unknown disturbing factors and retaining useful in formation and intrinsic individual differences in organisms.In addition,it can also prevent the overfitting of model and make the subsequent statistical analysis more reliable." @default.
- W2361920909 created "2016-06-24" @default.
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- W2361920909 date "2012-01-01" @default.
- W2361920909 modified "2023-09-24" @default.
- W2361920909 title "Metabolomics Data Filtering Method Based on PCA" @default.
- W2361920909 hasPublicationYear "2012" @default.
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