Section: Partnerships and Cooperations
IDEALG (ANR/PIA-Biotechnology and Bioresource)
Participants : Meziane Aite, Arnaud Belcour, Marie Chevallier, François Coste, Clémence Frioux, Jeanne Got, Jacques Nicolas, Anne Siegel.
The project gathers 18 partners from Station Biologique de Roscoff (coordinator), CNRS, IFREMER, UEB, UBO, UBS, ENSCR, University of Nantes, INRA, AgroCampus, and the industrial field in order to foster biotechnology applications within the seaweed field. Dyliss is co-leader of the WP related to the establishment of a virtual platform for integrating omics studies on seaweed and the integrative analysis of seaweed metabolism. Major objectives are the building of brown algae metabolic maps, metabolic flux analysis and the selection of symbiotic bacteria for brown algae. We will also contribute to the prediction of specific enzymes (sulfatases and haloacid dehalogenase) [More details]. 2012-20. Total grant: 11M€. Dyliss grant: 534k€.
PEPS: a platform for supporting studies in pharmaco-epidemiology using medico-administrative databases (ANSM)
Participants : Olivier Dameron, Yann Rivault.
The project involves EHESP (coordinator) (public health, Rennes), Univ. Rennes 1 (including the Dyliss), INSERM, CESP and CHU Rennes. The project goal is to develop generic methods supporting efficient and semantically-rich queries for pharmaco-epidemiology studies on medico-administrative databases. 2015-2018. Total grant: 3,6M€. Lacodam & Dyliss grant: 145k€.
TGFSysBio (ITMO Cancer)
Participants : Olivier Dameron, Maxime Folschette, Vijay Ingalalli, Jacques Nicolas, Anne Siegel, Nathalie Théret, Pierre Vignet.
Partners are INSERM (coordinator) (IRSET, Univ. Rennes 1) CNRS (Dyliss team) and Inria (Antique, Paris). The TGFSYSBIO project aims at developing the first model of extracellular and intracellular TGF-beta system by combining a ruled-based modelling approach (kappa) and a Petri net modelling approach (cadbiom). 2015-18. Total grant: 418k€. Dyliss grant: 129k€.
Programs funded by Inria
IPL Algae in silico
Participants : Meziane Aite, Arnaud Belcour, François Coste, Jeanne Got, Anne Siegel.
This project involves mainly the inria teams Biocore (coordinator), Ange and Dyliss . Microalgae are recognized for the extraordinary diversity of molecules they can contain: proteins, lipids (for biofuel or long chain polyunsaturated fatty acids for human health), vitamins, antioxidants, pigments. The project aims at predicting and optimizing the productivity of microalgae. Dyliss is in charge of the identification of physiological functions for microalgae based on their proteomes, which is undergone through the reconstruction of the metabolic network of the T. lutea microalgae. Dyliss is also working with the the inria team Pleiade on learning and predicting the specificities of desaturase enzymes in Ostreococcus tauri green algae. 2014-18.
Participants : Olivier Dameron, Anne Siegel.
This project involves mainly the inria teams Aramis (coordinator) Dyliss, Genscale and Bonsai. The project aims at identifying the main markers of neurodegenerative pathologies through the production and the integration of imaging and bioinformatics data. Dyliss is in charge of facilitating the interoperability of imaging and bioinformatics data. 2017-20.
FederatedQueryScaler (Exploratory Research Action)
Participants : Olivier Dameron, Xavier Garnier, Vijay Ingalalli.
This project is coordinated by Dyliss and is a common project with the Wimmics Inria team. This project aims at developing automatic generation of abstractions for biological data and knowledge in order to scale federated queries in the context of semantic web technologies. 2017-2018.
Participants : Olivier Dameron, Xavier Garnier, Guillaume Alviset, Anne Siegel.
AskOmics [url] is a visual SPARQL query interface supporting both intuitive data integration and querying while avoiding the user to face most of the technical difficulties underlying RDF and SPARQL. The underlying motivation is that even though Linked (Open) Data now provide the infrastructure for accessing large corpora of data and knowledge, life science end-users seldom use them, nor contribute back their data to the LOD cloud by lack of technical expertise. AskOmics aims at bridging the gap between end users and the LOD cloud. 2018-2020.