AI Article Synopsis
- Recent advances in analytical techniques like LC-MS are producing large and complex datasets in metabolomics, requiring effective analysis methods.
- Pathway analysis tools, such as Mummichog, help interpret these datasets by connecting them to relevant biological contexts and diseases.
- This chapter serves as both an overview and practical guide to common pathway analysis tools, providing examples of mapping techniques and their applications in label-free metabolomics.
Article Abstract
Recent advances in analytical techniques, particularly LC-MS, generate increasingly large and complex metabolomics datasets. Pathway analysis tools help place the experimental observations into relevant biological or disease context. This chapter provides an overview of the general concepts and common tools for pathway analysis, including Mummichog for untargeted metabolomics. Examples of pathway mapping, MetScape, and Mummichog are explained. This serves as both a practical tutorial and a timely survey of pathway analysis for label-free metabolomics data.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1007/978-1-0716-0239-3_19 | DOI Listing |
Publication Analysis
Top Keywords
pathway analysis
16
untargeted metabolomics
8
pathway
5
analysis targeted
4
targeted untargeted
4
metabolomics
4
metabolomics advances
4
advances analytical
4
analytical techniques
4
techniques lc-ms
4
Similar Publications
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!