Development of algorithms or rule-based tools for identification of metabolites from high resolution mass spectral trees

The aim of this project is to develop a novel semi-automatic strategy for the identification of relevant human metabolites in body fluids and tissues using multi-stage mass spectra (MSn) data. MSn data provides comprehensive structural chemistry information of the parent ion of interest, since it encloses fragments generated from the particular parent ion. However, there are neither flexible tools nor accessible platforms for processing MSn data on the market that are accessible to our needs. Within this project different algorithms, tools, a MSn database and platform are developed to enable proper processing and retrieval of chemical structural information from the acquired multi-stage spectral data. In parallel, all this knowledge will be stored in a database that can be used for the assignment of metabolites already present in the database or, at least, for the partial elucidation of metabolites not registered in the database yet (de-novo identification). For that, a search engine specific for comparing MSn data and extraction of partial MSn data will be implemented.
All the algorithms, tools, and the implemented platform will be free accessible for the metabolomics community through a web page application. The NMC-Data Support Platform will also integrate most of these features.
 

Main project title: 
Algorithms for substructures using MS
AIO/PD: 
PD 1-6-08
Researcher: 
Principal Investigator: 
Code 1: 
MI2
Status Project Proposal: 
Approved
Start date: 
Projected end date: