ResearchBioinformatics was born of the need to use methods derived from computer science for the processing of information in the context of biology. It constitutes a wide field of multidisciplinary research where biology, mathematics, computer science, physics provide crucial elements for research. This field has been in a constant mutation since its birth following the evolution of the methods of biology. The origin of bioinformatics is certainly linked to the analysis of the sequence in order to compare the sequences between them, then to annotate the genomes, to predict the genes, their structures and their regulatory regions allowing the construction of small networks genetic. The appearance of the DNA chips allowed a first evolution of the problems of the bioinformatics. By the possible quantification of thousands of transcripts, functional biology changes scale. It has been therefore necessary to create the tools to analyze this data and to understand the functioning of the organism. This is a first attempt to understand the dynamics of regulatory networks. Finally, systems biology seeks to apprehend a biological system not as the sum of its constituent elements but as a system in its own right. It seeks to account for the emergence of certain phenomena (a system is more than the sum of its parts), sensitivity to certain parameters, in short, the complexity of biological systems. It tries to establish methods and techniques that enable us to understand biological systems, their complexity, to construct and manipulate biological systems. This involves understanding the structure of genetic networks, metabolic networks and signal transduction networks, understanding their dynamics, and eliciting methods to control, construct and modify these systems to satisfy certain properties. The evolution of my research follows the same pattern as the bioinformatics.
The modeling of complex biological systems that seemed to me unavoidable when biologists asked us questions about the dynamics of regulatory networks. We were the first to develop formal approaches to assist in the search for discrete model parameters, and then we proposed some hybrid approaches to take into account the temporal aspects. A study of Boolean functions is then indispensable to understand the cutting-upthat can be made in the modeling of the networks of genes. At the same time, we have developed a modeling framework to take into account geometric aspects. Currently I address 3 main themes all concerning the modelling process for biological complex systems
- Determining parameters for discrete and hybrid models of gene networks.
- symbolic reasonning on gene networks
- Machine learning for toxicology.
Current Research Areas:See the webpage on the research activity "Formal Bioinfo"
Determining parameters for discrete and hybrid models of gene networks, symbolic reasonning on gene networks, Extensions and applications of formal methods to assist in the formal modeling of gene regulatory networks, model-checking in bioinformatics, test methods, constraint approaches, graph transformation for bioinformatics of biological systems, Machine learning for toxicology.
" Biologists can be divided into two classes: experimentalists who observe things that cannot be explained, and theoreticians who explain things that cannot be observed. " - Aharon Katzir-Katchalsky