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

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Searched keyword : Genome assembly

Related people (5)


Emna has joined the C3BI in 2016 and worked actively in the IGDA platform doing research and education. Now, she is also part of the Viral Populations and Pathogenesis Unit (PVP).

Genome assemblySequence analysisProgram developmentData integrationRead mappingLIMSParallel computingGene predictionShotgun metagenomics

Projects (1)


Group : DETACHED - Detached : Biomics

I joined the Bioinformatics and Biostatistics Hub at Institut Pasteur in 2016 where I am currently developing pipelines related to NGS for the Biomics Pôle. I have an interdisciplinary research experience: after a PhD in Astronomy (gravitational wave data analysis), I joined several research institute to work in the fields of plant modelling (INRIA, Montpellier, 2008-2011), System Biology — in particular logical modelling (EMBL-EBI Cambridge, U.K., 2011-2015), and drug discovery (Sanger Institute, Cambridge, U.K.), 2015). On a daily basis, I use data analysis and machine learning techniques within high-quality software to tackle scientific problems.

AlgorithmicsData managementData VisualizationGenome assemblyGenomicsMachine learningModelingScientific computingDatabases and ontologiesSofware development and engineeringData and text miningIllumina HiSeqGraph theory and analysisIllumina MiSeq

Projects (2)


Group : GIPHY - Embedded : PIßnet

| work as a research engineer in the ßioinƒormatics and ßiostatistics HUß of the |nstitut Pasteur. Holder of a PhD in bioinƒormatics, my main interest is on ƒast but robust phylogenetic inƒerence algorithms and methods ƒrom large genome-scaled datasets. |n consequence, | am oƒten involved in related bioinƒormatics projects, such as perƒorming de novo or ab initio genome assemblies, designing and processing core genome †yping schemes, building and analysing phylogenomics datasets, or implementing and distributing novel tools and methods.

AlgorithmicsClusteringGenome assemblyGenomicsGenotypingPhylogeneticsTaxonomyGenome analysisProgram developmentEvolutionSequence homology analysis

Projects (19)


Group : PLATEFORM - Detached : Biomics

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

Projects (18)


2015 – . – Institut Pasteur, Paris, France – Unit : Bioinformatics and Biostatistics HUB 2012 – 2015 – Institut Pasteur, Paris, France – Unit : Molecular Genetics of Yeasts Supervisor : Prof. B. Dujon 2012 – Institut Pasteur, Paris, France – Unit : Integrated Mycobacterial Pathogenomics Supervisor: Dr. R. Brosch Education 2012– MSc. Bioinformatics – Université Paris Diderot (Paris VII)

Genome assemblySequence analysisGenome analysisOrthology and paralogy analysisRead mappingSequence homology analysisDNA structure analysisGenome rearrangementsMotifs and patterns detection
Saccharomyces cerevisiae
Projects (24)

Related projects (16)

viral evolution around Ebola Treatment Centre in Macenta and according to disease outcomes

The 2013-2015 Ebola virus disease epidemic is the largest outbreak so far described with 27 305 cases and 11 169 deaths. The virus spread by human to human contact throughout Western Africa and never before has a variant been transmitted for such a sustained period of time. Ebola virus are RNA virus so as other RNA viruses they could accumulate mutations during evolution. Therefore it is an emergency to monitor viral changes and adaptation within and between individuals in order to help researchers to better understand susceptibility to Ebola infections, to guide research on therapeutic targets and to ensure accurate diagnosis. New technologies can provide information about pathogen’s evolution and in our lab we have access to an Ion PGMTM sequencer. Thanks to the national reference center for viral hemorrhagic fever (VHF) we have at our disposal a large number of samples collected from Ebola infected patients especially from Guinea. We have developed an Amplicon approach using sixteen couples of specific primers for Ebola viruses and a RNA sequencing method based on randomly primed cDNA synthesis to product our libraries. Ion PGMTM Hi-Q sequencing kit will be used to sequence up to 400 bp inserts loaded onto 316v2TM or 318v2TM chip. Through high depth sequencing we would like to follow up the profiling of intra and inter host viral quasispecies at different time of the epidemic in the geographic area of the Ebola Treatment Centre in Macenta. Thanks to the activities of national reference center for VHF and the Biomics Pole one aim of the project is also to occasionally compare viral quasispecies and consensus sequences between patients who get uncommon symptoms from those who get classical illness and to study intra host quasispecies in different biological fluids (cerebrospinal fluid, sperm, urine) to see if there are differences between persistent species and viral quasispecies found during symptomatic step.

Project status : Closed

How ribosomal protein gene position impacts in the genome evolution during a long term evolution experiment.

Increasing evidence indicates that nucleoid spatiotemporal organization is crucial for bacterial physiology since these microorganism lack a compartmentalized nucleus. However, it is still unclear how gene order within the chromosome can influence cell physiology. In silico approaches have shown that genes involved in transcription and translation processes, in particular ribosomal protein (RP) genes, tend to be located near the replication origin (oriC) in fast-growing bacteria suggesting that such a positional bias might be an evolutionarily conserved growth-optimization strategy. Recently we systematically relocated a locus containing half of ribosomal protein genes (S10) to different genomic positions in Vibrio cholerae. These experiments revealed drastic differences in growth rate and infectivity within this isogenic strain set. We showed that genomic positioning of ribosomal protein genes is crucial for physiology by providing replication-dependent higher dosage in fast growing conditions. Therefore it might play a key role in genome evolution of bacterial species. We aim at observing how the genomic positioning of these genes would influence the evolution of Vibrio cholerae. To gain insight into the evolutionary consequences of relocating RP genes, we let evolve either the wild type or the most affected strains for 1000 generations in fast-growing conditions. NGS will be performed and analyzedon the evolved populations to understand the genetic changes responsible of the observed phenotypic changes.

Project status : Pending

A reference panel of dengue vector genomes

Dengue prevention relies primarily on controlling populations of the main mosquito vector, Aedes aegypti, which is failing in many parts of the world because of the lack of sustained commitment of resources and ineffective implementation. Novel entomological approaches to dengue control are being developed that aim at replacing or suppressing mosquito vector populations. Insufficient genomic resources for Ae. aegypti, however, have until now impeded progress in both basic and applied research on this medically important mosquito species. The only available reference genome for Ae. aegypti is a draft that consists of over 4,800 unassembled fragments with incomplete annotation. Moreover, the inbred Ae. aegypti laboratory strain that was sequenced does not universally represent the considerable genetic and ecological diversity of the species worldwide. The large size of the genome and its high content in repeat-rich sequences of transposable elements was a major difficulty to assemble the Ae. aegypti genome sequence. In the present project, we aim to overcome this difficulty using a novel strategy for genome sequencing and assembly. The ultimate goal is to produce several, fully assembled, well-annotated, new Ae. aegypti reference genomes from epidemiologically relevant populations. The expected outcome is a genome reference panel including a catalog of species-wide genetic variation that will significantly improve genomic resources for Ae. aegypti research and help address a broad range of biological questions related to Ae. aegypti vectorial capacity and dengue virus transmission.

Project status : Closed