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Predicting Network Activity from High Throughput Metabolomics.
- Source :
-
PLoS Computational Biology . Jul2013, Vol. 9 Issue 7, p1-11. 11p. - Publication Year :
- 2013
-
Abstract
- The functional interpretation of high throughput metabolomics by mass spectrometry is hindered by the identification of metabolites, a tedious and challenging task. We present a set of computational algorithms which, by leveraging the collective power of metabolic pathways and networks, predict functional activity directly from spectral feature tables without a priori identification of metabolites. The algorithms were experimentally validated on the activation of innate immune cells. [ABSTRACT FROM AUTHOR]
- Subjects :
- *METABOLOMICS
*MASS spectrometry
*COMPUTER algorithms
*METABOLITES
*NATURAL immunity
Subjects
Details
- Language :
- English
- ISSN :
- 1553734X
- Volume :
- 9
- Issue :
- 7
- Database :
- Academic Search Index
- Journal :
- PLoS Computational Biology
- Publication Type :
- Academic Journal
- Accession number :
- 89626406
- Full Text :
- https://doi.org/10.1371/journal.pcbi.1003123