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GENSCALE Research team

Scalable, Optimized and Parallel Algorithms for Genomics

  • Leader : Dominique Lavenier
  • Type : Project team
  • Research center(s) : Rennes
  • Field : Digital Health, Biology and Earth
  • Theme : Computational Biology
  • Partner(s) : CNRS,Université Rennes 1,École normale supérieure de Rennes
  • Collaborator(s) : Institut de recherche en informatique et systèmes aléatoires (IRISA) (UMR6074)

Team presentation

During the last 10 years, biotechnologies experienced a great development which drastically reshaped the approach to research in disciplines such as bio-sciences. Biological information can be nowadays obtained by the analysis of large databases containing high-throughput sequencing data. Novel algorithms must be developed in such a way they are able to recognize and manage the challenges related to the analysis of the data acquired by such modern technologies.

In this context, the main research performed by the GenScale team is focused on the analysis of large-scale genomic data. Main tasks of the members of the team include the development of suitable algorithms that are optimized in terms of CPU time and memory requirements, and which can also be executed in parallel environments.

Our work is performed in strong collaboration with other bio-sciences research teams (agronomy, ecology, health).

Research themes

The comparison of biological objects is one of the main interests in bioinformatics. Therefore, our research is performed by following these three research axes:

  • Sequence comparison:
    • large-scale annotation
    • analysis of meta-genomics
  • Genome comparison:
    • local: research of variants (SNPs, indels, …)
    • global: comparative genomics
  • Structure comparison:
    • classification of protein families

These research axes are integrated with other research activities (assembly) which allows for generating some biological objects of interest from high-throughput sequencing data.

International and industrial relations

  • University of Chile, Santiago, Chile
  • Colorado State University, USA
  • CWI, Algorithmic Computational Biology, Amsterdam, Netherlands
  • Sofia University, Bulgaria
  • Federal University of Rio de Janeiro, Rio de Janeiro, Brazil Laboratório Nacional de Computação Científica, Petropolis, Brazil
  • Dept. of Mathematics, Statistics and Scientific Computing, UNICAMP, Campinas, Sao Paulo, Brazil
  • GenomeQuest :
  • Korilog :
  • Kalray :

Keywords: Bioinformatics genomic parallelism scalability optimization