Summary of Study ST001873
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001182. The data can be accessed directly via it's Project DOI: 10.21228/M8XD6P This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.
Study ID | ST001873 |
Study Title | Metabolomics analysis of multiple samples on AB 5600-Part 1 |
Study Type | Metabolomics |
Study Summary | Metabolomics analysis of multiple samples from human, trying to annotate the metabolites in them. AB SCIEX 5600+ was used for metabolomics detection. |
Institute | Dalian Institute Of Chemical Physics |
Laboratory | Laboratory of High Resolution Separation/Analysis and Metabonomics |
Last Name | Zheng |
First Name | Fujian |
Address | No. 457 Zhongshan Road, Shahekou District, Dalian, Liaoning Province, China |
zhengfj@dicp.ac.cn | |
Phone | 18698730176 |
Submit Date | 2021-06-18 |
Raw Data Available | Yes |
Raw Data File Type(s) | wiff |
Analysis Type Detail | LC-MS |
Release Date | 2021-07-24 |
Release Version | 1 |
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Project:
Project ID: | PR001182 |
Project DOI: | doi: 10.21228/M8XD6P |
Project Title: | Metabolomics analysis of multiple samples |
Project Summary: | Liquid chromatography–high resolution mass spectrometry (LC-HRMS) is the most popular platform for untargeted metabolomics methods, but annotating LC-HRMS data is a long-standing bottleneck that we are facing since years ago in metabolomics research. A wide variety of methods have been established to deal with the annotation issue. To date, however, there is a scarcity of efficient, systematic, and easy-to-handle tools that are tailored for metabolomics and exposome community. Herein, we developed a user-friendly and powerful stand-alone software, MetEx, to enable implementation of classical peak detection-based annotation and a brand-new annotation method based on targeted extraction algorithms. Especially the newly proposed annotation method of targeted extraction can identify more than 2 times more metabolites than traditional peak detection-based annotation methods because it reduces the loss of metabolite signal in the data preprocessing process. |
Institute: | Dalian Institute of Chemical Physics |
Laboratory: | Laboratory of High Resolution Separation/Analysis and Metabonomics |
Last Name: | Zheng |
First Name: | Fujian |
Address: | 457 Zhongshan Road Dalian, China 116023, Dalian, Liaoning, 116021, China |
Email: | zhengfj@dicp.ac.cn |
Phone: | 18698730176 |