Projects

Last projects : 

Ancient mitochondrial genomics: 

MiSeq NGS data analysis of 7th and 8th century samples (Nîmes)

  • Mitochondrial genome SNPs
  • Y chromosome SNPs

http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0148583 

 

Compost microflora metagenomics for Bioethanol production : 

Metagenomic NGS data analyses (DNA and RNA): sequence filtering, assembly, species composion analysis, gene prediction, binning, exploratory database development)
https://services.cbib.u-bordeaux2.fr/biomines/

 

COSMOS

The Framework Programme 7 EU Initiative ‘coordination of standards in metabolomics’ (COSMOS http://cosmos-fp7.eu/) is developing a robust data infrastructure and exchange standards for metabolomics data and metadata. We contribute to this effort by developing the XEML-lab framework for management of echophysiological data (https://github.com/cbib/XEML-Lab). 

 

VARIATIONS ANALYSIS OF PACBIO DATA

We develop MICADo, a de Bruijn graph based method that makes possible to distinguish between patient specific mutations and other alterations (cohort specific mutations and sequencing errors) for targeted sequencing of a cohort of patients (https://github.com/cbib/MICADo).

 

Strawberry plants

Characterization of genetic elements involved in strawberry plant continuous flowering. 

  • Mutation enumeration in EMS mutants
  • de novo sequence assemby of polyploid strawberry genome to fill a gap between 2 homeologous BACs

 

SuperClass

The SuperClass project aims to develop new acquisition, quantification and classification methods for HCS super-resolution microscopy. We expect to provide an integrated solution for classification of receptor behaviour based on their dynamics. 

 

COBRA

This is an EU PlantKBBE project that aims at the identification of genetic factors of susceptibility to  viral infection in order to provide new opportunities to protect plants against these diseases. In particular, we develop a plant-virus knowledgebase and a computational method for susceptibility gene prediction.
https://services.cbib.u-bordeaux2.fr/cobra/ 

 

Metagenomics for inflammatory diseases

Analysis of 16S data from patients’ samples of various inflammatory disorders (ankylosing spondylitis, mucoviscidosis, …)