Literature DB >> 15260896

Bioinformatics for glycomics: status, methods, requirements and perspectives.

Claus-Wilhelm von der Lieth1, Andreas Bohne-Lang, Klaus Karl Lohmann, Martin Frank.   

Abstract

The term 'glycomics' describes the scientific attempt to identify and study all the glycan molecules - the glycome - synthesised by an organism. The aim is to create a cell-by-cell catalogue of glycosyltransferase expression and detected glycan structures. The current status of databases and bioinformatics tools, which are still in their infancy, is reviewed. The structures of glycans as secondary gene products cannot be easily predicted from the DNA sequence. Glycan sequences cannot be described by a simple linear one-letter code as each pair of monosaccharides can be linked in several ways and branched structures can be formed. Few of the bioinformatics algorithms developed for genomics/proteomics can be directly adapted for glycomics. The development of algorithms, which allow a rapid, automatic interpretation of mass spectra to identify glycan structures is currently the most active field of research. The lack of generally accepted ways to normalise glycan structures and exchange glycan formats hampers an efficient cross-linking and the automatic exchange of distributed data. The upcoming glycomics should accept that unrestricted dissemination of scientific data accelerates scientific findings and initiates a number of new initiatives to explore the data.

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Year:  2004        PMID: 15260896     DOI: 10.1093/bib/5.2.164

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  20 in total

1.  Glycoproteomics: protein modifications for versatile functions. Meeting on glycoproteomics.

Authors:  Reiko T Lee; Gordan Lauc; Yuan C Lee
Journal:  EMBO Rep       Date:  2005-11       Impact factor: 8.807

2.  Automated interpretation of MS/MS spectra of oligosaccharides.

Authors:  Haixu Tang; Yehia Mechref; Milos V Novotny
Journal:  Bioinformatics       Date:  2005-06       Impact factor: 6.937

3.  PRISMOID: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact.

Authors:  Fuyi Li; Cunshuo Fan; Tatiana T Marquez-Lago; André Leier; Jerico Revote; Cangzhi Jia; Yan Zhu; A Ian Smith; Geoffrey I Webb; Quanzhong Liu; Leyi Wei; Jian Li; Jiangning Song
Journal:  Brief Bioinform       Date:  2020-05-21       Impact factor: 11.622

4.  Informatics Ecosystems to Advance the Biology of Glycans.

Authors:  Lewis J Frey
Journal:  Methods Mol Biol       Date:  2022

Review 5.  Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2003-2004.

Authors:  David J Harvey
Journal:  Mass Spectrom Rev       Date:  2009 Mar-Apr       Impact factor: 10.946

Review 6.  Bioinformatics and molecular modeling in glycobiology.

Authors:  Martin Frank; Siegfried Schloissnig
Journal:  Cell Mol Life Sci       Date:  2010-04-04       Impact factor: 9.261

7.  Employment of tandem mass spectrometry for the accurate and specific identification of oligosaccharide structures.

Authors:  Shuai Wu; Juli Salcedo; Ning Tang; Keith Waddell; Rudolf Grimm; J Bruce German; Carlito B Lebrilla
Journal:  Anal Chem       Date:  2012-08-21       Impact factor: 6.986

8.  EUROCarbDB: An open-access platform for glycoinformatics.

Authors:  Claus-Wilhelm von der Lieth; Ana Ardá Freire; Dennis Blank; Matthew P Campbell; Alessio Ceroni; David R Damerell; Anne Dell; Raymond A Dwek; Beat Ernst; Rasmus Fogh; Martin Frank; Hildegard Geyer; Rudolf Geyer; Mathew J Harrison; Kim Henrick; Stefan Herget; William E Hull; John Ionides; Hiren J Joshi; Johannis P Kamerling; Bas R Leeflang; Thomas Lütteke; Magnus Lundborg; Kai Maass; Anthony Merry; René Ranzinger; Jimmy Rosen; Louise Royle; Pauline M Rudd; Siegfried Schloissnig; Roland Stenutz; Wim F Vranken; Göran Widmalm; Stuart M Haslam
Journal:  Glycobiology       Date:  2010-11-23       Impact factor: 4.313

9.  Centralized modularity of N-linked glycosylation pathways in mammalian cells.

Authors:  Pan-Jun Kim; Dong-Yup Lee; Hawoong Jeong
Journal:  PLoS One       Date:  2009-10-05       Impact factor: 3.240

10.  In silico platform for prediction of N-, O- and C-glycosites in eukaryotic protein sequences.

Authors:  Jagat Singh Chauhan; Alka Rao; Gajendra P S Raghava
Journal:  PLoS One       Date:  2013-06-28       Impact factor: 3.240

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