The role of informatics in glycobiology research with special emphasis on automatic interpretation of MS spectra

Biochim Biophys Acta. 2006 Apr;1760(4):568-77. doi: 10.1016/j.bbagen.2005.12.004. Epub 2005 Dec 29.

Abstract

This paper reviews the current status of bioinformatics applications and databases in glycobiology, which are based on bioinformatics approaches as well as informatics for glycobiology where an explicit encoding of glycan structures is required. The availability of the complete sequence of the human genome has accelerated the systematic identification of so far unidentified glycogenes considerably in many areas of glycobiology using well-established bioinfomatics tools. Although there has been an immense development of new glyco-related data collections as well as informatics tools and several efforts have been started to cross-link and reference the various data deposited in distributed databases, informatics for glycobiology and glycomics is still poorly developed compared to the genomics and proteomics area. The development of algorithms for the automatic interpretation of MS spectra - currently, a severe bottleneck, which hampers the rapid and reliable interpretation of MS data in high-throughput glycomics projects - is reviewed. A comprehensive list of web resources is given. Several lines of progression are discussed. There is an urgent need for the development of decentralised input facilities of experimentally determined glycan structures. Simultaneously, agreements of standards for the structural description of glycans as well as formats for the related data have to be established. The integration of glycomics with genomics/proteomics has to increase.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Computational Biology / methods*
  • Databases, Nucleic Acid
  • Enzymes / genetics
  • Glycoproteins / chemistry
  • Humans
  • Internet
  • Mass Spectrometry*
  • Polysaccharides / analysis
  • Polysaccharides / biosynthesis*

Substances

  • Enzymes
  • Glycoproteins
  • Polysaccharides