MetCCS predictor: a web server for predicting collision cross-section values of metabolites in ion mobility-mass spectrometry based metabolomics

In metabolomics, rigorous structural identification of metabolites presents a challenge for bioinformatics. The use of collision cross-section (CCS) values of metabolites derived from ion mobility-mass spectrometry effectively increases the confidence of metabolite identification, but this technique...

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Bibliographic Details
Published inBioinformatics (Oxford, England) Vol. 33; no. 14; pp. 2235 - 2237
Main Authors Zhou, Zhiwei, Xiong, Xin, Zhu, Zheng-Jiang
Format Journal Article
LanguageEnglish
Published England 15.07.2017
Subjects
Mass Spectrometry - methods
Metabolomics - methods
Software
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Summary:In metabolomics, rigorous structural identification of metabolites presents a challenge for bioinformatics. The use of collision cross-section (CCS) values of metabolites derived from ion mobility-mass spectrometry effectively increases the confidence of metabolite identification, but this technique suffers from the limit number of available CCS values. Currently, there is no software available for rapidly generating the metabolites' CCS values. Here, we developed the first web server, namely, MetCCS Predictor, for predicting CCS values. It can predict the CCS values of metabolites using molecular descriptors within a few seconds. Common users with limited background on bioinformatics can benefit from this software and effectively improve the metabolite identification in metabolomics. The web server is freely available at: http://www.metabolomics-shanghai.org/MetCCS/ . jiangzhu@sioc.ac.cn. Supplementary data are available at Bioinformatics online.
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ISSN:1367-4803
1367-4811
DOI:10.1093/bioinformatics/btx140