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Functional Glycomics pp 269–281Cite as

Bioinformatics in Glycomics: Glycan Characterization with Mass Spectrometric Data Using SimGlycan™

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 600))

Abstract

Mass spectrometry (MS), with its low sample requirement and high sensitivity, has been the predominantly used methodology for characterization and elucidation of glycan structures. However, manual interpretation of MS data is complex and tedious due to large number of product ions observed and also due to the variation in their m/z values under various experimental conditions. We present an automated tool, SimGlycan™, for this purpose, which accepts raw/standard MS data files as input and characterizes the associated glycan structure with high accuracy using database searching and scoring techniques. Not only does it predict the glycan structure using an MS/MS database searching technique, but it also facilitates predicting novel glycans by drawing a glycan and mapping it onto an experimental spectrum to check the degree of proximity between the theoretical and the experimental glycans. It serves as a platform for developing advanced tools that may be used for glycopeptide identification using MS data and 3D structural analysis of glycans with a few improvements in the existing features.

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Author information

Authors and Affiliations

  1. PREMIER Biosoft International, Palo Alto, CA, USA

    Arun Apte & Ningombam Sanjib Meitei

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  1. Arun Apte
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  2. Ningombam Sanjib Meitei
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Editors and Affiliations

  1. Inst. Biological Sciences, National Research Council Canada, Sussex Drive 100, Ottawa, K1A 0R6, Canada

    Jianjun Li

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© 2010 Humana Press

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Apte, A., Meitei, N.S. (2010). Bioinformatics in Glycomics: Glycan Characterization with Mass Spectrometric Data Using SimGlycan™. In: Li, J. (eds) Functional Glycomics. Methods in Molecular Biology, vol 600. Humana Press. https://doi.org/10.1007/978-1-60761-454-8_19

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  • DOI: https://doi.org/10.1007/978-1-60761-454-8_19

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  • Publisher Name: Humana Press

  • Print ISBN: 978-1-60761-453-1

  • Online ISBN: 978-1-60761-454-8

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