The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
MetPA: a web-based metabolomics tool for pathway analysis and visualization
Abstract
Summary: MetPA (Metabolomics Pathway Analysis) is a user-friendly, web-based tool dedicated to the analysis and visualization of metabolomic data within the biological context of metabolic pathways. MetPA combines several advanced pathway enrichment analysis procedures along with the analysis of pathway topological characteristics to help identify the most relevant metabolic pathways involved in a given metabolomic study. The results are presented in a Google-map style network visualization system that supports intuitive and interactive data exploration through point-and-click, dragging and lossless zooming. Additional features include a comprehensive compound library for metabolite name conversion, automatic generation of analysis report, as well as the implementation of various univariate statistical procedures that can be accessed when users click on any metabolite node on a pathway map. MetPA currently enables analysis and visualization of 874 metabolic pathways, covering 11 common model organisms. Availability: Freely available at http://metpa.metabolomics.ca Contact: david.wishart@ualberta.ca
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Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
A novel signaling pathway impact analysis
Tarca, A. L., Draghici, S., Khatri, P., Hassan, S. S., Mittal, P., Kim, J.-S., Kim, C. J., Kusanovic, J. P., & Romero, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btn577 · Cited by 1,031
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Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis
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Lee, D. Y., Kim, E., & Choi, M. H. (2015) · BMB Reports · doi:10.5483/bmbrep.2015.48.4.275 · Cited by 484
Furman, D., Chang, J., Lartigue, L., Bolen, C. R., Haddad, F., Gaudilliere, B., Ganio, E. A., Fragiadakis, G. K., Spitzer, M. H., Douchet, I., et al. (2017) · Nature Medicine · doi:10.1038/nm.4267 · Cited by 389
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Sugimoto, M., Kawakami, M., Robert, M., Soga, T., & Tomita, M. (2012) · Current Bioinformatics · doi:10.2174/157489312799304431 · Cited by 307
Omics approaches for understanding heavy metal responses and tolerance in plants
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Metadata
- Authors
- Xia, J., & Wishart, D. S.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-07-13
- Volume
- 26
- Issue
- 18
- Pages
- 2342-2344
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2167540852
- Cited by
- 766
- References
- 2
- FWCI
- 4.73
- Type
- journal article
- Language
- en
- Open access
- closed
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