GenScale

Acronyme ou nom de la structure
Nom complet (en toutes lettres)
Scalable, Optimized and Parallel Alforithms for Genomics
Tutelle(s) institutionnelle(s) et affiliation/labelisation
Prénom et nom du responsable de l'équipe
Pierre Peterlongo
E-mail de contact
pierre.peterlongo@inria.fr
Adresse

35000 Rennes
France

Coordonnées GPS
48.115886, -1.63911
Téléphone
02 99 84 72 17
Description

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.

GenScale research is organized along four main axes:

  • Data structures
    • Indexing the mass of genomic data
    • Focus on the de-Bruijn graph structure.
    • Provide end-user and optimized library
  • Algorithms
    • Optimized (time and memory) tools dedicated to NGS processing
    • Data compression, genome assembly, variant detection, metagenomics, GWAS (genome-wide association Study)
  • Parallelism
    • Combine several levels of parallelism
    • Use existing techniques as multithreading or MapReduce
    • Constrained algorithmic development, in particular, targeting hardware accelerators
  • Applications
    • Participate in biology-oriented projects
    • Inra, CEA, National Museum, Hospitals, …

 

 

Description (English)

GenScale is a bioinformatics research team. Its main goal is to develop scalable methods, tools, and software forprocessing 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.

GenScale research is organized along four main axes:

  • Data structures
    • Indexing the mass of genomic data
    • Focus on the de-Bruijn graph structure.
    • Provide end-user and optimized library
  • Algorithms
    • Optimized (time and memory) tools dedicated to NGS processing
    • Data compression, genome assembly, variant detection, metagenomics, GWAS (genome-wide association Study)
  • Parallelism
    • Combine several levels of parallelism
    • Use existing techniques as multithreading or MapReduce
    • Constrained algorithmic development, in particular, targeting hardware accelerators
  • Applications
    • Participate in biology-oriented projects
    • Inra, CEA, National Museum, Hospitals, …

 

 

Type de structure
Equipe de recherche
Adhésion en tant que personne morale
Activé