Design, simulate and evaluate complex breeding processes using stochastic methods. After defining strategy with the customer and analyzing pilot data including costs, strategies to set-up and evaluate short-, mid- and long-term breeding programs are defined and simulated as an aid to decision making. Plant and animal industry is considered.
Quantitative and molecular genetics computations: Linkage mapping, QTL analysis, Genome-wide-Association Studies, Genomic prediction, analysis of complex data, experimental design. Plant and animal industry is considered.
Linking bioinformatics and computational methods in quantitative genetics to improve profitability of research actions. Developing high capacity, high quality pipelines to optimize data flow and decision in breeding processes for companies.
Development of bio-statistical methods to evaluate performances of crops and wild species. Selective breeding for agricultural species or adaptation to natural changes for wild species are key parameters for managing changes. We develop innovative methods using multiple source of information – soil, climate, biological processes, genome data – to predict current and future performances of plant species.