Projects

Translational informatics

Development of a computational infrastructure dedicated to the integrated analysis of data from "-omics" sciences (cf. www.omics-ethics.org/ fr/definition-science-omics) related to human genetic diseases and health. This infrastructure includes algorithms and original methods, such as:

• Algorithms and workflows for structural bioinformatics, in the context of a project financed by the French Bioinformatics Institute (IFB), coordinated by P. Tufféry (RPBS, Paris) and D. Ritchie (Loria, Nancy).
• Algorithms for integrative structural biology, in the context of ongoing funded projects, including the European INSTRUCT research infrastructure for 'Integrative Structural Biology' and the French ANR Investments for the Future project: FRISBI, coordinated by Bruno Klaholtz, IGBMC, Strasbourg.
• Multi-scale methods for a better understanding of protein properties (structure, interactions, dynamics...) and better integration of the heterogenous data associated with a protein or a family of proteins. Ongoing project, BIPBIP, funded by French ANR in collaboration with Annick Dejaegere, IGBMC, Strasbourg.
• Evolutionary analyses of protein sequences from NGS data, applied to health, in collaboration with the Data_Mining data mining and SONIC teams.
• GREMSAP (GRid Evolutionary Multiple Sequence Alignment Platform), in collaboration with the SONIC team, l’Institut des Systèmes Complexes Paris Île de France, l’Institut de Neurobiologie Albert Fressard.
• Social Network Clinical Database for Intellectual Disabilities: Development of a social network for patients, related to genetic diseases causing developmental disabilities, in collaboration with the SONIC team, the Translational medicine & neurogenetics team, IGBMC, led by Jean-Louis Mandel, and the [http:/www.ucad.sn Cheikh Anta Diop University, Senegal].
• Infrastructure for 'big data' management for the translational analysis of mutations involved in human genetic disease. BIRD/SM2PH-central is aimed at the integration of heterogeneous data (genomic, phenotypic, evolution, cellular networks,...), with data mining methods (association rules, inductive logic programming,...), and includes the design of a semantic query language (BIRD-QL) and the development of original graphical interfaces. These developments are done in collaboration with Hoan Ngyugen, IGBMC, Strasbourg.

Systems bioinformatics

Development of research in the field of biological systems analysis, to understand genotype-phenotype relationships, notable concerning genetic diseases, and the study of complex biological systems, for example in various cancers or rare diseases (ciliopathies, myopathies,...) in close collaboration with the Human Genetics Laboratory, led by Hélène Dollfus (www.unistra.fr/index.php?id=19264&L=3). The originality of our approach lies in the extraction and exploitation of evolutionary information (sequence analysis, comparative genomics, etc.) in order to improve the analysis of the different levels of complexity in biological systems. Some examples of systems-level projects:

• Analysis of macromolecular complexes (TFIID...) in collaboration with the Department of Integrative structural biology, IGBMC.
• Analysis of organelles (exosome, endosome...) in collaboration with the membrane traffic and lipid signaling team, GMGM: synthetic yeast evolution, the characterization of the shared / specific features at different levels (nucleotide, gene, pathway), the identification of correlations between the evolutionary scenarios and the modifications identified in the molecular processes.
• Genomic analysis of 1000 myopathy patients (Myocapture project and ongoing FRM-funded project, in collaboration with le team of Jocelyn Laporte, IGBMC) with the goal of identifying and characterizing new genes in these diseases.
• Analysis of genomic data from ciliopathy patients (Bardet-Biedl Syndrome and Alström Syndrome) to identify the genes responsible for the diseases, and to understand the links between genotypes/phenotypes, in collaboration with Human Genetics Laboratory, led by Hélène Dollfus.
• Integration of "omics" data to develop a new generation of the Vaccinia virus (VACV). Ongoing funded project (OncoVaccine: ANR Recherches Partenariales et Innovation Biomédicale) in collaboration with TRANSGENE, the HTCS platform led by Laurent Brino, IGBMC and the team of Etienne Weiss, IREBS, Strasbourg.
• ImAnno is a collaborative project between the LBGI and teams at the IGBMC, Strasbourg (P. Dollé) and the Institute of Vision, Paris (J. Sahel, T. Leveillard) aimed at developing an ergonomic and integrative annotation tool for biological images (ISH, fundus...). Once annotated, the images allow to access all the knowledge extraction tools implemented or developed by the LBGI, including protein-protein interaction networks, tools for automatic analysis of the evolution, transcriptomic data, etc.
• Multi-scale tempo-spatial modeling of the primary cilia as a means of communication (intracellular transport, physical cell-cell interactions, environmental sensory system) and its role in the cell cycle, development, as well as the evolution of eukaryotic organisms, in collaboration with the Digital Campus for Complex Systems.

Artifical Evolution and Complex Systems

ECOMAPS (Evolutionary Computation on Massively Parallel Systems)

The purpose of the ECOMAPS project is to revisit the different evolutionary paradigms in order to adapt them to massive parallelism, notably on General Purpose Graphic Processing Units (GPGPUs) and to integrate them into the EASEA language(click here for a rapid introduction).

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It consists of 3 axes:

Continued development of the language EASEA (EAsy Specification of Evolutionary Algorithms, (Collet et al., 2001) allowing an evolutionary algorithm to be executed on GPGPU cards General Purpose Graphic Processing Unit without the programmer needing to know how to programme the cards. The development of the platform for massively parallel evolutionary calculations EASEA is currently done by :

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• Ogier Maitre for evolutionary algorithms and genetic programming, and
• Frédéric Kruger for CMA-ES (Covariance Matrix Adapatation Evolutionary Strategy, used for continuous problems), thememetic algorithms(hybrid algorithms with a local search for Lamarkian evolution) and island parallelisation on clusters of hybrid machines.

The EASEA platform integrates the latest algorithmic developments of the team. It is available at Sourceforge.

- Adaptation of Linear Genetic Programming to execution on GPGPU cards

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Linear Genetic Programming, developed by Wolfgang Banzhaf (cf. Brameier & Banzhaf, 2007) is especially well adapted to the GPU processor architecture. Ogier Maitre and Wolfgang Banzhaf are modifying Linear Genetic Programming to exploit the specificities of these massively parallel cards. The results will be integrated in the EASEA language (cf. below).

- Implementation of an algorithm for virtual chemistry on GPGPU

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Virtual chemistry is a paradigm that canbe used not only to simulate chemical reactions, but also to resolve scientific problems. The topic of the post-doc of Lidia Yamamoto involves porting virtual chemistry to GPU cards.

ARA (Administrateur Réseaux Artificiel)

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The post-doc of Deepak Sharma financed by OSEO for the company Kelerio. Kelerio manages networks for corporate customers. The purpose of the ARA project is to create an Artificial Network Administrator capable of detecting and correcting malfunctions before they occur.

A collaboration is ongoing on this subject with Cécilia Zanni-Merck and Philippe.bouche3 Philippe Bouché of LGeCo (INSA of Strasbourg)

RENZEO (Recherche de Nouvelles Zéolites)

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Internship of M2 ILC Research option, following an M1 internship in collaboration with Laurent Baumes of the "Instituto de Tecnologia Quimica" of the Polytechnic University of Valencia (Spain). Zeolites are porous crystalline structures of great importance in industry. Depending on the pore diameter of the molecule, a zeolite may be used as an adsorbent, to filter or retain other molecules, thereby dehydrating gas or as a catalyst. Each new discovery of a zeolite allows new industrial uses, hence the importance of research in this field

BETON (Optimisation of concrete structures)

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Cédric den Drijver is conducting an apprenticeship training course funded by INSA Strasbourg in the context of a collaboration related to the thesis of Céline Conrardy funded by Lafarge. The goal of this learning is to optimize concrete structures (beams, for example) by Genetic Programming on GPGPU by evaluating them by finite elements.