» Articles » PMID: 16459020

The Role of Informatics in Glycobiology Research with Special Emphasis on Automatic Interpretation of MS Spectra

Overview
Specialties Biochemistry
Biophysics
Date 2006 Feb 7
PMID 16459020
Citations 19
Authors
Affiliations
Soon will be listed here.
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.

Citing Articles

Informatics Ecosystems to Advance the Biology of Glycans.

Frey L Methods Mol Biol. 2021; 2303:655-673.

PMID: 34626414 DOI: 10.1007/978-1-0716-1398-6_50.


Insights into Bioinformatic Applications for Glycosylation: Instigating an Awakening towards Applying Glycoinformatic Resources for Cancer Diagnosis and Therapy.

Muthu M, Chun S, Gopal J, Anthonydhason V, Haga S, Devadoss A Int J Mol Sci. 2020; 21(24).

PMID: 33302373 PMC: 7762546. DOI: 10.3390/ijms21249336.


Computational approaches to define a human milk metaglycome.

Agravat S, Song X, Rojsajjakul T, Cummings R, Smith D Bioinformatics. 2016; 32(10):1471-8.

PMID: 26803164 PMC: 4907376. DOI: 10.1093/bioinformatics/btw048.


The use of glycoinformatics in glycochemistry.

Lutteke T Beilstein J Org Chem. 2012; 8:915-29.

PMID: 23015842 PMC: 3388882. DOI: 10.3762/bjoc.8.104.


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

Wu S, Salcedo J, Tang N, Waddell K, Grimm R, German J Anal Chem. 2012; 84(17):7456-62.

PMID: 22867103 PMC: 3555499. DOI: 10.1021/ac301398h.