A New Comprehensive Platform for Profile-Mode-Based Untargeted Metabolomics for Efficient Data Mining to Improve Compound Extraction and Identification

文献类型： 外文期刊

第一作者： Wang, Xing-Cai

作者： Wang, Xing-Cai;Yang, Chang;She, Yuanbin;Zhai, Meng;Lv, Hang;Ma, Hui;Yu, Yong-Jie;Li, Shu-Fang;Zheng, Qing-Xia;Liu, Ping-Ping;Lu, Peng;Fu, Hai-Yan

作者机构：

期刊名称：ANALYTICAL CHEMISTRY （ 影响因子：6.7； 五年影响因子：6.6 ）

ISSN： 0003-2700

年卷期： 2025 年 97 卷 27 期

页码：

收录情况： SCI

摘要： The profile mode of ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) is commonly utilized in metabolomics for its ability to comprehensively retain compound information in mass spectra. However, current data-analysis methods have not been optimized for the entire profile-mode-based untargeted metabolomics. To address this issue, we developed a set of novel algorithms, including centroiding transformation, extracted ion chromatogram construction, and feature extraction. We integrated them into a new automatic data analysis platform, AntDAS-Profiler. The performance of these newly developed algorithms was demonstrated by distinguishing chrysanthemums from various production origins. Additionally, AntDAS-Profiler was comprehensively compared with several state-of-the-art tools such as MS-DIAL, XCMS, and MZmine. Results suggested that AntDAS-Profiler can provide researchers with a comprehensive solution for UHPLC-HRMS profile-mode-based metabolomics. AntDAS-Profiler can be accessed at http://www.pmdb.org.cn/antdasprofiler.

分类号：

  • 相关文献
作者其他论文 更多>>

微信小程序