Analyzing LC/MS Metabolic Profiling Data in the Context of Existing Metabolic Networks
Document Type
Article
Publication Date
2013
Abstract
Metabolic profiling is the unbiased detection and quantification of low molecular-weight metabolites in a living system. It is rapidly developing in biological and translational research, contributing to disease mechanism elucidation, environmental chemical surveillance, biomarker detection, and health outcome prediction. Recent developments in experimental and computational technology allow more and more known metabolites to be detected and quantified from complex samples. As the coverage of the metabolic network improves, it has become feasible to examine metabolic profiling data from a systems perspective, i.e. interpreting the data and performing statistical inference in the context of pathways andgenome-scale metabolic networks. Recently a number of methods have been developed in this area, and much improvement in algorithms and databases are still needed. In this review, we survey some methods for the analysis of metabolic profiling data based on metabolic networks.
Publication Title
Current Metabolomics
Volume
1
Issue
1
First Page
84
Last Page
91
Recommended Citation
Yu, Tianwei and Bai, Yun, "Analyzing LC/MS Metabolic Profiling Data in the Context of Existing Metabolic Networks" (2013). PCOM Scholarly Works. 1019.
https://digitalcommons.pcom.edu/scholarly_papers/1019
Comments
This article was published in Current Metabolomics, Volume 1, Issue 1, Pages 84-91.
The published version is available at dx.doi.org/10.2174/2213235X11301010084.Copyright © 2013 Bentham.