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Meta-analysis of LC-MS data in metabolomic studies is desired to determine overlaps and differences among various experiments. For example, in large metabolic biomarker discovery studies involving hundreds of samples, it may be necessary to conduct multiple experiments, each involving a subset of the samples due to technical limitations. The ions selected from each experiment are analyzed to determine...
Metabolite identification is the major bottle-neck in LC-MS based metabolomic investigations. The mass-based search approach often leaves a large fraction of metabolites with either no identification or multiple putative identifications. As manual verification of metabolites is laborious, computational approaches are needed to obtain more reliable putative identifications and prioritize them. In this...
Mass spectrometry-based metabolomics is getting mature and playing an ever important role in the systematic understanding of biological process in conjunction with other members of “-omics” family. However, the identification of metabolites in untargeted metabolomics profiling remains a challenge. In this paper, we propose a support vector machine (SVM)-based spectral matching algorithm to combine...
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