Revealing disease-associated pathways by network integration of untargeted metabolomics

Revealing disease-associated pathways by network integration of untargeted metabolomics

Uncovering the molecular context of dysregulated metabolites is crucial to understand pathogenic pathways. However, their system-level analysis has been limited owing to challenges in global metabolite identification. Most metabolite features detected by untargeted metabolomics carried out by liquid...

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Bibliographic Details
Main Authors: Leidl, Mathias (Author), Avila-Pacheco, Julian (Author), Pirhaji, Leila (Contributor), Milani, Pamela (Contributor), Curran, Timothy G. (Contributor), Clish, Clary (Contributor), Saghatelian, Alan (Contributor), Fraenkel, Ernest (Contributor), White, Forest M. (Author)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Biological Engineering (Contributor), Massachusetts Institute of Technology. Department of Biology (Contributor), White, Forest M (Contributor)
Format: Article
Language:English
Published: Springer Nature, 2018-09-05T17:26:25Z.
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