Interdisciplinary Research Center on Biology and Chemistry, and Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, People's Republic of China.
Bioinformatics. 2017 Jul 15;33(14):2235-2237. doi: 10.1093/bioinformatics/btx140.
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/ .
Supplementary data are available at Bioinformatics online.
在代谢组学中,对代谢物进行严格的结构鉴定对生物信息学提出了挑战。使用离子淌度-质谱衍生的代谢物的碰撞截面(CCS)值可有效提高代谢物鉴定的可信度,但该技术受到可用 CCS 值数量的限制。目前,尚无用于快速生成代谢物 CCS 值的软件。在这里,我们开发了第一个网络服务器,即 MetCCS Predictor,用于预测 CCS 值。它可以在几秒钟内使用分子描述符预测代谢物的 CCS 值。具有有限生物信息学背景的普通用户可以从该软件中受益,并有效地提高代谢组学中的代谢物鉴定能力。
该网络服务器可免费使用:http://www.metabolomics-shanghai.org/MetCCS/ 。
补充数据可在“Bioinformatics”在线获取。