Bernard Gibaud et Olivier Dameron
Titre : Vers des ontologies pour décrire des biomarqueurs d’imagerie :
pourquoi et comment ?
The presentation will introduce imaging biomarkers, and stress
their importance in biomedical research (both in clinical and translational research) as well in key decisions concerning patient management. In this context, the deployment and federation of imaging biobanks should provide the basic infrastructure to support the sharing of biomedical imaging data (including imaging biomarkers), and stimulate research about biomarkers’ design, qualification and clinical use.
Ontologies and other semantic web technologies could facilitate the sharing of this information. The presentation will review some of the ontology sources currently available or in development, and discuss their relevance (e.g. OBI, RadLex, QIBO, OntoNeuroLog). The most salient open issues will be listedh.
Titre : Knowledge-based selection of candidate metabolic networks : application (in progress) to Ectocarpus siliculosus.
The idealg project aims at having a better overall understanding of the three groups of macroalgae (green, red and brown) in order to develop the algae sector in Brittany. This includes especially the study of species specific to each of the three major groups of algae, Ectocarpus siliculosus in the case of brown algae. A part of this projects consists in proposing a complete metabolic network for Ectocarpus siliculosus. A metabolic network is the complete set of physical and physiological reactions that explain the overall functioning of a cell. This metabolic network has to have a good quality and has to be compatible with biological observations. It must especially be able to explain the presence of 51 compounds identified as interesting by biologists. Ectocarpus siliculosus not being a "model species ", numerous portions of metabolic pathways are unknown. We used MetaCyc as a source of candidate reactions to complete the metabolic network. The smallest set of reactions necessary for producing the 51 target proteins of interest is composed of 70 reactions. However, a systematic exploration produced 2400 possible minimal sets. Each of them is composed of 52 reactions, and together they cover 70 reactions. We analyzed the topology of these 70 reactions and used symbolic knowledge to select the most desirable reactions, reducing the number of candidate networks from 2400 to 48 (-98%).
Vous pouvez retrouver toutes les informations sur la page du séminaire Biosticker.