Section: Partnerships and Cooperations

National Initiatives

ANR

Amis-ARN , ANR BLANC 2009-2012: Graph Algorithms and Automatic Softwares for Interactive RNA Structure Modelling. This project is being coordinated by Amib . The two other ivolved groups are from Prism (Versailles University) and E. Westhof's lab (Strasbourg University). We aim to do substantial progress in the problem of automatically or semi-automatically modelling the three-dimensional structure of RNA molecules, given their sequence. By semi-automatically we mean developing algorithms and software that can automatically propose (good) solutions, and that can efficiently compute alternative solutions according to some new constraints or some new hypotheses given by the expert modeler. More precisely, we plan to work on the three following points:

1. Development of computational methods for solving some key steps necessary for modelling RNA 3D structures. These methods will rely on new graph algorithms for molecular structures and on biological expertise on sequence-structure relations in RNA molecules.

2. Implementation of these methods in a software suite, Paradise , which is being developed by one of the partners (E. Westhof's lab, Strasbourg University) and which will be made freely available to the scientific community.

3. Application of these methods in order to model several molecules of interest.

ANR-Magnum , ANR BLANC 2010-2014: Algorithmic methods for the non-uniform random generation: Models and applications. The central theme of the Magnum project is the elaboration of complex discrete models that are of broad applicability in several areas of computer science. A major motivation for the development of such models is the design and analysis of efficient algorithms dedicated to simulation of large discrete systems and random generation of large combinatorial structures. Another important motivation is to revisit the area of average-case complexity theory under the angle of realistic data models. The project proposes to develop the general theory of complex discrete models, devise new algorithms for random generation and simulation, as well as bridge the gap between theoretical analyses and practically meaningful data models. The sophisticated methods developed during the past decades make it possible to enumerate and quantify parameters of a large variety of combinatorial models, including trees, graphs, words and languages, permutations, etc. However these methods are mostly targeted at the analysis of uniform models , where, typically, all words (or graphs or trees) are taken with equal likelihood. The Magnum project proposes to depart from this uniformity assumption and develop new classes of models that bear a fair relevance to real-life data, while being, at the same time, still mathematically tractable. Such models are the ones most likely to be connected with efficient algorithms and data structures.

Inria-Inra

Amib and Inra-Tours (A. Poupon) are partners in a two years project Asam . This project aims to help the understanding of signalling pathways involving G protein-coupled receptors (GPCR) which are excellent targets in paramacogenomics research. Large amounts of experiments are available in this context while globally interpreting all the experimental data remains a very challenging task for biologists. The aim of Asam is thus to provide means to semi automatically construct signalling networks of GPCRs . In particular, Asam aims to base its solution on the design of a knowledge base containing expert rules able to interpret various experimental results and semi automatically construct signalling networks. Interestingly, each piece of the network (a piece of data or a relationship between pieces of data) may be associated with quality information depending on various criteria (a piece of data obtained by various experiments or by experiments of high quality etc.).