Poste d'ingénieur (IE/IR) Development of network integration database, methods and tools for metabolomics

Type de poste
Niveau d'étude minimal
Dates
Durée du poste
Contrat renouvelable
Contrat non renouvelable
Date de prise de fonction
Date de fin de validité de l'annonce
Localisation
Nom de la structure d'accueil
Adresse

180 Chemin de Tournefeuille
31027 Toulouse
France

Contacts
Fabien Jourdan
Clément Frainay
Email du/des contacts
Fabien.Jourdan@inrae.fr
Clement.Frainay@inrae.fr
Description

Keywords: Bioinformatics, Network Science, Semantic web technology, Graph database, Metabolomics

International grant: This research project is included in an internationally funded grant (ANR-DFG, 928k€) between 4 leading labs in the field of metabolomics in France and Germany. Funding includes travel grants (possibility to stay few weeks in the different labs), functioning and publishing costs.

Multidisciplinary research: the proposed research project is fully computational but the postdoc will work closely with chemists and biologists. Application fields will also be broad from model organism (C. Elegans), plants to human.

Work in a Bioinformatics, Network Science, Semantic web technology, Graph database, Metabolomicscomputational biology group: The Toxalim team gathers 9 bioinformatics scientists with various skills (modelling, machine learning, web programming, graph algorithms…). Together with a strong network in France and beyond the team develop original methods and tools (e.g. MetExplore web server). Importantly we aim at maintaining a friendly and supportive work environment (social events, hackathons). Details on the group can be found here:

https://sites.google.com/site/fabienjourdan/inra-xenobiotics

Overall objective: integrate networks in metabolomics. Metabolism is a key system in any living organism and its understanding can help in tackling many health and environmental issues. In this context, metabolomics is a cornerstone method to produce observational data on metabolism. Nevertheless, this approach still faces several challenges among which: improving metabolite annotation, biochemical reaction description and data interpretation. Network science is playing a major role in this context. But currently networks are of various sources (experimental or knowledge based) and it is necessary to integrate them in order to go further in our understanding of metabolism.

Creating a computational system for network integration. The first aim will be to create a modular and flexible computational system to integrate the networks. Beyond data storage, information visualization and query engine, the system should support programmatic graph navigation and operation in order to integrate higher level information extraction technics based on graph algorithm.

Equipe adhérente personne morale SFBI
Equipe Non adhérente