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• W2159072321 abstract "Abstract Motivation: Glycosylation is one of the most important post-translational modifications of proteins and explains some aspects of the diversification of higher organisms not explained by template-driven synthesis. For glycomics to mature as much as genomics and proteomics, the necessary tools need to be developed and tested. Liquid chromatography-mass spectrometry is one of the gold standards for oligosaccharide analysis and leads to large amounts of data, not easily interpreted manually. We present a study on the testing and validation of statistical analysis tools to aid the structural elucidation of these analyses as well as using the results to answer biologically relevant questions. Results: We show the usefulness of data reduction and statistical analysis in the interpretation of complex glycosylation data. The reduction does not result in the loss of importance of the glycosylation information as shown by comparison of control and disease samples in two tissue types. Contact: catherine.hayes@medkem.gu.se Supplementary information: Supplementary data are available at Bioinformatics online." @default.
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• W2159072321 date "2012-04-28" @default.
• W2159072321 modified "2023-09-26" @default.
• W2159072321 title "Statistical analysis of glycosylation profiles to compare tissue type and inflammatory disease state" @default.
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• W2159072321 doi "https://doi.org/10.1093/bioinformatics/bts242" @default.
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