INRIA

Post-Doctoral Position on Novel algorithms for annotating and fitting of electron density

<p style="margin-top: 0px; margin-bottom: 2px; text-align: center; font-size: 12px; font-family: Arial; min-height: 14px;"><b style="letter-spacing: 0px;">Post-doctoral Fellow Opening</b></p><p style="margin-top: 0px; margin-bottom: 2px; text-align: center; font-family: Arial;"><span style="letter-spacing: 0.0px"><b>Novel algorithms for annotating and fitting of electron density</b></span></p><p style="margin-top: 0px; margin-bottom: 2px; text-align: justify; font-size: 9px; font-fami

Post-Doctoral Position on Novel FFT Docking Techniques

<h2 style="margin: 0px 0px 10px; padding: 0px; border: 0px; font-family: 'Yanone Kaffeesatz', arial, helvetica, sans-serif; font-size: 30px; line-height: 22px; vertical-align: baseline; color: rgb(34, 34, 34); background-color: rgb(255, 255, 255);">Development of a Novel Exhaustive&ndash;Search FFT&ndash;Based Method With a Very Detailed Potential for Protein Docking</h2><p style="margin-top: 0px; margin-bottom: 25px; padding: 0px; border: 0px; font-family: sans-serif; font-size: 14px; line-height: 22px; vertical-align: baseline; color: rgb(51

Dyliss

Acronyme ou nom de la structure
Nom complet (en toutes lettres)
DYnamics, Logics and Inference for biological Systems and Sequences
Adresse

IRISA & INRIA Rennes
Bat 12A
Campus de Beaulieu

35042 Rennes cedex
France

Téléphone
0299847100
Description (English)

Dyliss is a research team in bioinformatics. We focus on sequence analysis and systems biology. We use qualitative formal systems to characterize genetic actors from non model species, such as algae or mining baceria, that control phenotypic answers when challenged by their environment.

  • Methods: constraint logic programming, symbolic dynamics, machine learning, formal systems.
  • Expertise: functional characterization, non-model species, multi-scale integration.
  • Application domains: marine biology, micro-environmental biology...

The main computational challenge is to face lacks and incompleteness in both expert knowledge and experimental observations. Our strategy relies on three main points.

  • We focus on a targeted functional characterization rather than on a complete understanding of the species.
  • We rely on knowledge rather than on amounts of experimentations.
  • We use model-species to validate methods.

We use qualitative formal systems for knowledge acquisition and integration. All our methods aim at identifying the space of all models that are consistent with both knowledge and observations. Then we provide tools to navigate in this space in order to investigate which properties are shared by a large proportion of the space.

SFBI
Membre de la SFBI

GenScale

Acronyme ou nom de la structure
Nom complet (en toutes lettres)
Scalable, Optimized and Parallel Alforithms for Genomics
Adresse

35000 Rennes
France

Téléphone
02 99 84 72 17
Fax
02 99 84 71 71
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, …

 

 

SFBI
Membre de la SFBI