The BioIntelligence Project
|The BioIntelligence Project|
|Category:||Contracts and Grants with Industry|
The objective of the "BioIntelligence" project is to design an integrated framework for the discovery and the development of new biological products. This framework takes into account all phases of the development of a product, from molecular to industrial aspects, and is intended to be used in life science industry (pharmacy, medicine, cosmetics, etc.). The framework has to propose various tools and activities such as:
- a platform for searching and analyzing biological information (heterogeneous data, documents, knowledge sources, etc.),
- knowledge-based models and process for simulation and biology in silico,
- the management of all activities related to the discovery of new products in collaboration with the industrial laboratories (collaborative work, industrial process management, quality, certification).
Moreover, the "BioIntelligence" project is aimed at designing software modules for helping the biological daily practice and to guide knowledge discovery, knowledge representation and management, and finally innovation and production. The "BioIntelligence" project is led by "Dassault Systèmes" and involves industrial partners such as Sanofi Aventis, Laboratoires Pierre Fabre, Ipsen, Servier, Bayer Crops, and two academics, Inserm and Inria. The kickoff meeting took place in Sophia-Antipolis between July 5th and 6th 2010.
Two thesis related to "BioIntelligence" are beginning in the Orpailleur team. The first one is in concern with ontology engineering for biology. Two main aspects which are considered at the moment are ontology matching and ontology mining for the design of ontology design patterns (involving graph mining methods). Among web resources, ontologies take a special place as they materialize models of the real-world, they provide the representation of domain knowledge, and they allow domain knowledge manipulation and dissemination. One objective of the thesis is to study and to design a complete process for discovering in heterogeneous resources domain models representing significant parts of these resources. Such models are also called ontology design patterns and are intended to be used as building blocks that can be interconnected for building a working domain ontology, based on a set of reusable components. Ontologies lying at the NCBO BioPortal will be considered as a training set for the thesis work.
The second thesis is related to the study of possible combination of mining methods on biological data. The mining methods which are considered here are based on FCA and RCA, itemset and association rule extraction, and inductive logic programming. These methods have their own strengths and provide different special capabilities for extending domain ontologies. A particular attention will be paid to the integration of heterogeneous biological data and the management of a large volume of biological data while being guided by domain knowledge lying in ontologies (linking data and knowledge units). Practical experiments will be led on biological data (clinical trials data and cohort data) also in accordance with ontologies lying at the NCBO BioPortal.