Our goal is to develop algorithms and methods for molecular biology. Generally speaking, we seek to leverage large-scale data produced by biology, such as genomes, transcriptomes (DNA or sequential chips), interactomes and proteomes. Advances in methodology are essential for processing this data in a relevant and effi cient manner. At the same time, these advances are fundamental for other issues and methods of general interest.

Fields of methodological investigation, and tools, are related to the following areas:

  Text and tree algorithmics, combinatorics, optimization
  Statistics, probabilities, learning, data analysis, classification.

Key biological applications include:

  Phylogenesis and phylogenomics, evolution models, tree of life, biodiversity
  Comparative genomics, genomic rearrangements, cancer
  Functional genomics, transciptomes, proteomes, Plasmodium falciparum (malaria)
  Evolution of pathogens, AIDS
  Very high-speed sequencing