Hub members Have many expertise, covering most of the fields in bioinformatics and biostatistics. You'll find below a non-exhaustive list of these expertise
Searched keyword : Targeted metagenomics
Related people (2)
After a PhD in informatics on graph analysis (metabolic networks and sRNA-mRNA interaction graphs) at the LaBRI (Université de Bordeaux), I joined the DSIMB team (INTS) for a post-doc on structural modeling. Then, I performed a second post-doc at Metagenopolis – INRA Jouy-en-Josas, where I was initiated to the analysis of metagenomic data. I was recruited at the HUB in 2015, and since I pursue the development of methods dedicated to the treatment of metagenomic data by combining either the treatment of sequencing data, the statistics, the protein structural modeling and the graph analysis.
AlgorithmicsClusteringGenome assemblyGenomicsMetabolomicsModelingNon coding RNASequence analysisStructural bioinformaticsTargeted metagenomicsDatabaseGenome analysisBiostatisticsProgram developmentScientific computingDatabases and ontologiesExploratory data analysisData and text miningIllumina HiSeqComparative metagenomicsRead mappingIllumina MiSeqSequence homology analysisGene predictionMultidimensional data analysisSequencingShotgun metagenomics
- Targeted search of specific commensals in 16S databases(Pamela SCHNUPF - Molecular Microbial Pathogenesis) - In Progress
- Microbiota dysbiosis in human colon cancer(Iradj SOBHANI - Other) - Pending
- Environmental and human surveillance of polioviruses, VDPVs, and other enteroviruses in Madagascar and the impact during the switch from tOPV to bOPV(Patsy POLSTON - Biology of Enteric Viruses) - In Progress
After a diploma of statistician engineer from the Ensai (Ecole Nationale de la Statistique et de l’Analyse de l’Information) and a Ph.D in applied mathematics in the Statistics & Genome lab (AgroParisTech), I worked as a developer for the XLSTAT software. I have implemented some statistical methods such as mixture models, log-linear regression, mood test, bayesian hierarchical modeling CBC/HB, … Then I worked as a head teacher in statistics for one year. I was recruited in the Bioinformatic and biostatistic hub of the C3BI (Center of Bioinformatics, Biostatistics and Integrative Biology) in 2014, I am in charge of the statistical analysis and the development of R/R shiny pipelines.
Machine learningStatistical inferenceTargeted metagenomicsBiostatisticsApplication of mathematics in sciencesStatistical experiment design
Related projects (2)
The gastrointestinal tract of humans is colonized by hundreds of microbial species, - bacteria, archaebacterial, fungi, protozoa and viruses -, collectively named the gut microbiome. The intestinal commensal bacteria have an important role in metabolic processes and contribute to colonization resistance against intestinal pathogens. Fungi are usually considered to be a minor component of the global microbiome. However, the mycobiome (fungal component of the entire microbiome) has been in fact little studied particularly with regards to its relationships with the other components of the microbiome. Fungi could be important players of the microbiome because some fungal species are able to proliferate in response to diet or during dysbiosis due to antibiotic treatment or gut inflammation. The aim of this project is to investigate the effect of specific antibiotics (primarily anti-Gram negative bacteria antibiotic) on the gut mycobiome. More specifically, we will examine the impact of cefotaxime and ceftriaxone, 2 antibiotics with same antimicrobial spectra but different rates of biliary elimination, on the changes in fungal communities.
Bacteria analysis of fecal samples by 16S sequencing has provided a wealth of information for the distribution of bacterial species in both health and disease conditions. When looking at bacterial com