Missing value imputation for LC-MS metabolomics data by incorporating metabolic network and adduct ion relations

摘要

Motivation: Metabolomics data generated from liquid chromatography-mass spectrometry platforms often contain missing values. Existing imputation methods do not consider underlying feature relations and the metabolic network information. As a result, the imputation results may not be optimal.