Section: Research Program

Combinatorial discrete models and algorithms

Our research is driven by biological questions. At the same time, we have in mind to develop well-founded models and efficient algorithms. Biological macromolecules are naturally modelled by various types of discrete structures: String, trees, and graphs. String algorithms is an established research subject of the team. We have been working on spaced seed techniques for several years [13] , [20] , [22] , [16] , [15] . Members of the team have also a strong expertise in text indexing and compressed index data structures  [21] , [24] , [23] . Such methods are widely-used for the analysis of biological sequences because they allow a data set to be stored and queried efficiently. Ordered trees and graphs naturally arise when dealing with structures of molecules, such as RNAs  [25] , [19] , [18] , [17] , [11] or non-ribosomal peptides [12] . The underlying questions are: how to compare molecules at structural level, how to search for structural patterns ? String, trees and graphs are also useful to study genomic rearrangements: Neighborhoods of genes can be modelled by oriented graphs, genomes as permutations, strings or trees.

High-performance computing is another tool that we use to achieve our goals. It covers several paradigms: grids, single-instruction, multiple-data (SIMD) instructions or manycore processors such as graphics cards (GPU). For example, libraries like CUDA and OpenCL also facilitate the use of these manycore processors. These hardware architectures bring promising opportunities for time-consuming bottlenecks arising in bioinformatics.