SYSMET: INTEGRATIVE SYSTEMS METABOLOMICS
This project aims to address this challenge using a new software tool (SysMet) that utilizes a network-based approach to uncover relationships between disease and metabolites by investigating the rewiring and conserved interactions among metabolites in the progression of the disease. In addition, we propose to extend the networ-based approach for integrative analysis of multi-omic data to identify disease-associated metabolites. The tool will contribute to improving the ability of researchers to discover biomarkers by enhancing the role of metabolomics in systems biology research.
METABOQUEST: TOOL FOR METABOLITE IDENTIFICATION
This project seeks to develop a probabilistic framework that assigns a priority score to each putative metabolite ID by combining information from multiple resources including compound databases, pathways, biochemical networks, and spectral libraries. The proposed probabilistic model will exploit the inter-dependent relationships between metabolites in biological organisms based on knowledge derived from pathways and biochemical networks to assign priority score to each putative metabolite IDs. If MS/MS data are available, the score for a putative ID will take into account how well the measured MS/MS matches against those in spectral libraries or fragment patterns predicted by in-silico spectral interpretation. Successful implementation and validation of the model will enable users to accurately identify putative metabolite IDs and assign priority scores by taking advantage of publicly available databases, pathways, and biochemical networks, spectral libraries, as well as various tools designed for isotope/adduct recognition, decomposition of isotopic patterns, and in-silico spectral interpretation.