Our scientific  team finalized several research projects during  the last  5 years


  • From Integrative Biomarkers to Biologic Profile and Pharmaceutical Maps

      We create an integrative system of data analysis which allows the processing of non – homogeneous data and leads to data normalization and biomarkers discovery. The output of this system creates the basis of biologic profile parameters  and the so called “pharmaceutical maps”.

  • Modelling the neuroendocrine system: a dynamic structural framework

      Almost any disease is related with “a priori” or “a posteriori” interactions inside  the neuroendocrine system. Its modelling and comprehension has to be taken in account for a right understanding of the biological profile versus disease. We provide a dynamic structural network for applications.

  • Clustering Gene-Gene Interactions: biological and mathematical criteria to improve robustness

      Many clustering have been proposed in the literature involving gene interactions,  so the question of their robustness is opened. We obtained a gene-gene interaction clustering which follows the biological mapping, it is based on rigorous mathematical processing insuring the robustness and it is intuitive for the clinician confronted with omics data. 

  • Functional Analysis Methods to study physiological models: analytical solutions for kinetic enzymatic equations for personalized comprehension of elimination rate with applications in cancerology and toxicology

       The physiological models have for basis  differential equations that model the enzymatic processes. These equations  are very difficult to resolve. The existing methods are limited to the numerical approximation of solutions by algorithms of type Runge-Kutta. This approach leads to a loss of the variability in response from a person to another. We modeled the biological context with systemic  settings and we obtained analytical solutions to kinetic equations. This allows a personalized interpretation of results.


  • Modelling topological parameters for the tumors classification and treatment

      A tumor can be represented as a geometric object, so computational algebraic topology  analysis is an asset on understanding links between shapes, typologies and treatment. We create useful index for tumor monitoring.


  • Architectural Optimization to minimize the access time for Information Assembly in medical databases and inference methods for diagnosis and treatment

      We implemented a synthesis tool, which offer the possibility to see low level  information  made by omics – nucleotide, gene or protein-  at a higher level – metabolic pathway or physiological process. This tool involved research on new data structure, architecture and quick “real time” access algorithms.


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