Bioinformatics for glycomics: Status, methods, requirements and perspectives

C.-W. von der Lieth
2004 Briefings in Bioinformatics  
His main research interests are in molecular modelling and computational structural biology, with the main focus on glycobiology. Andreas Bohne-Lang is a computer scientist who has developed a variety of wellknown algorithms and web applications to encode, generate and represent structures of complex carbohydrates. Klaus Karl Lohmann is a pharmacist who has developed various algorithms and web applications assisting the automatic interpretation of mass spectra of complex carbohydrates. Martin
more » ... ohydrates. Martin Frank is a chemist. His main research interests are in molecular modelling and the application of advanced simulation techniques for structural biology. He has developed various computational approaches to efficiently explore the conformational space of glycans. 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.
doi:10.1093/bib/5.2.164 pmid:15260896 fatcat:eohemrrxcfgknjif54jzojlbmu