Section: New Results

Metabolic stories

Enumerating stories, i.e., enumerating maximal directed acyclic graphs with sets of sources and targets contained in a given subset of the nodes, is an algorithmic approach we proposed for interpreting metabolomics experiments. The modelling, algorithms and complexity results were recently accepted for publication [2] . The complexity of the enumeration problem remains unknown. There are also further modelling issues that could be dealt with in a near future. Both considerations were also detailed in a talk given in August at St. Petersburg, in the First RECOMB Satellite Conference on Open Problems in Algorithmic Biology.

We then applied our enumerating method on real data. We analysed data on the detoxification process of yeast cells exposed to cadmium. Our method allowed to recover known pathways involved in the process but also to propose alternative scenarios. The method was also investigated in order to automatically propose metabolic pathways through an experiment in which we try to recover known metabolic pathways using only minimal information (e.g., their entries and endpoints). A paper is in prepartion and should soon be submitted for publication. This work is being done in collaboration with Fabien Jourdan and Ludovic Cottret from the INRA at Toulouse, and with Christophe Junot from the CEA in Paris.