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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

GenScale is a bioinformatics research team. Its main goal is to develop scalable methods, tools, and software for processing genomic data. Our research is motivated by the fast development of next-generation sequencing (NGS) and third generation (TGS) technologies that provide very challenging problems both in terms of bioinformatics and computer sciences.

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

Research themes

GenScale research is organized along four main axes:

Data structures

  • Indexing the mass of genomic data
  • Focus on the de-Bruijn graph structure
  • Develop end-user optimized library

Algorithms

  • Time & memory optimzed tools dedicated to NGS processing
  • data compression, genome assembly, variant detection, metagenomics, GWAS

Parallelism

  • Multithreading, Vectorization (SSE, AVX, ...)
  • Hardware accelertor, Enhanced memory

Applications

  • Environnment
  • Health
  • Agronomy
 

International and industrial relations

International

  • Los Alamos, NM, USA
  • Sofia University, Bulgaria
  • ITN European project

Industry

  • UpMem, https://www.upmem.com/
  • Seenergi, http://www.seenergi.fr/
  • Enancio, https://www.enancio.fr/

Keywords: Bioinformatics genomic parallelism scalability optimization