Molecule Specific Normalization For Protein And Metabolite Biomarker Discovery
SAC '19: PROCEEDINGS OF THE 34TH ACM/SIGAPP SYMPOSIUM ON APPLIED COMPUTING(2019)
摘要
The paper proposes a molecule specific normalization algorithm, called MSN, which adopts a robust surface fitting strategy to minimize the molecular profile difference of a group of house-keeping molecules across samples. The house-keeping molecules are those molecules whose abundance levels were not affected by the biological treatment. The applications of the MSN method on two different datasets showed that MSN is a highly efficient normalization algorithm that yields the highest sensitivity and accuracy compared to five existing normalization algorithms
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关键词
Normalization,Robust Surface Fitting,Machine Learning,Loess Regression,Biomarker Discovery
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