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 : Biostatistics
Related people (15)
CV Senior Bioinformatician August 2015 – Present : Institut Pasteur, Paris PostDoc fellow 2011 – 2015 : Pascale Cossart’s laboratory, Unité des Interactions Bactéries-Cellules, Institut Pasteur, Paris Phd fellow 2007 – 2010 : Institut des Hautes Etudes Scientifiques, ann Ecole Normale Supérieure, Paris Magister of Science, Theoretical Physics 2003 – 2007 : Dynamical systems and statistics of complex matter, Université Paris 7 and Université Paris 6
BiophysicsMachine learningModelingProteomicsBiostatisticsDatabases and ontologiesHost-pathogen interactions
- Analysis of DNA methylation in the presence and absence of antibiotics in wt and mutant V. cholerae(Baharoglu ZEYNEP - Bacterial Genome Plasticity) - Closed
- Finding and Predicting CRISPR-Cas9 Efficiency(Jerome WONG NG - Synthetic Biology) - Closed
- Characterization of a Salmonella mutant carrying a single amino-acid substitution in the stress sigma factor RpoS(Françoise NOREL - Biochemistry of Macromolecular Interactions) - Closed
Developing and evaluating bioinformatic tools for: – next generation sequencing data – genome analysis & comparison Specialties:Genome & Transcriptome Bioinformatics
Data managementData VisualizationGenomicsNon coding RNASequence analysisTranscriptomicsGenome analysisBiostatisticsProgram developmentScientific computingData and text miningBiosensors and biomarkersEpidemiology and public health
- Tissue-resident stromal cell heterogeneity(Lucie PEDUTO - Stroma, Inflammation and Tissue Repair) - In Progress
- Role of small non coding RNAs in the adaptive response to oxidative stress in pathogenic Leptospira(NADIA BENAROUDJ - Biology of Spirochetes) - In Progress
- Dissecting Peptidoglycan pathways in human near-haploid cells(Martine FANTON D\'ANDON - Biology and Genetics of Bacterial Cell Wall) - Pending
Initially trained in evolutionary and environmental sciences, I studied population genetics and micro-evolutionary processes in a number of postdoctoral research projects. I recently joined the C3BI-Hub at the Institut Pasteur, where I work on various aspects involving Biostatistics and the analysis of genetic data.
Association studiesGenomicsGenotypingBiostatisticsGeneticsEvolutionPopulation genetics
BacteriaParasiteHumanInsect or arthropodOther animal
- Excess calorie intake early in life increases susceptibility to colitis in the adult(Ziad AL NABHANI - Microenvironment and Immunity) - In Progress
- Analysis of Internal Deletions in EV71(Bjoern MEYER - Viral Populations and Pathogenesis) - Pending
- 3D PATH(Marion RINCEL - Microenvironment and Immunity) - Pending
One of my projects consists in developing GRAVITY, a java tool based on Cytoscape to integrate genetic variants within protein-protein interaction networks to allow the visual and statistical interpretation of next-generation sequencing data, ultimately helping geneticists and clinicians to identify causal variants and better diagnose their patients. I’m also involved in several other projects in the lab, taking part in the design of pipelines for the processing and the analysis of genomics data, including SNP arrays, whole-exome and whole-genome sequencing data. This means being confronted to the big data problematic, the unit having to manage hundreds of terabytes of genomics data. Finally, I am now analysing these data in order to identify possible causes for autism, to help clinicians with their diagnosis but also to better understand the biological mechanisms at play in this complex disease. This is done through the project aiming at understanding the genetic architecture of autism in the Faroe Islands, and also with the newly starting IMI2 European project AIMS2-Trials.
AlgorithmicsData managementData VisualizationGenomicsMachine learningProteomicsGenome analysisBiostatisticsProgram developmentScientific computingApplication of mathematics in sciencesExploratory data analysisSofware development and engineeringData and text miningGenetics
I obtained an engineering degree in Biomedical engineering from Université de Technologie de Compiègne (UTC) in 1989, a master degree in Control of Complex Systems from UTC in 1990, a PhD in Control of Complex Systems from UTC in 1993, a University Degree in Human Genetics from The University of Rennes 1 in 2001 and a master degree in Functional Genomics from University Paris Diderot (Paris 7) in 2002. I worked as a statistician at the Transcriptome and Epigenome Platform from 2002 to 2017, where I was responsible for the statistical analyses of the data and had an important training activity (on the campus and outside). Since 2015 I have been co-head of the Bioinformatics and Biostatistics Hub within the Center of Bioinformatics, Biostatistics and Integrative Biology (C3BI). I am co-director of the Pasteur course Introduction to Data Analysis and co-organiser of the sincellTE summer school (a school dedicated to single cell transcriptome and epigenome data analysis). I am also co-managing the StatOmique group which gathers more than 60 statisticians from France.
RNA-seqStatistical inferenceTranscriptomicsBiostatisticsApplication of mathematics in sciencesExploratory data analysisIllumina HiSeqStatistical experiment designSequencing
- Biomarqueurs d’identification précoce du sepsis aux urgences (BIPS)(Jean-Marc CAVAILLON - Cytokines and Inflammation) - In Progress
- Study of the early pathogenesis during Lassa fever in cynomolgus monkeys and its correlation with the outcome(Sylvain BAIZE - Biology of Viral Emerging Infections) - In Progress
- Host microbiota modification by the pathogen Listeria monocytogenes(Javier PIZARRO-CERDA - Bacteria-Cell Interactions) - Closed + 1 project
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
- Characterization of the bacterial and fungal microbiota in Aedes aegypti natural breeding sites and larvae(Louis LAMBRECHTS - Insect-Virus Interactions) - Pending
- 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
Since September 2016, I am a research engineer in the Bioinformatics and Biostatistics HUB of the Institut Pasteur and detached in the Proteomics facility. I have a PhD in Signal Processing from the Ecole Nationale Supérieure des Télécommunications de Bretagne (Telecom Bretagne) and a Master in Mathematics with a specialty in Statistical Engineering from Rennes 1 University. After my PhD, I was a research and teaching assistant in Mathematics at the Institut National des Sciences Appliquées (INSA) of Rennes, then I worked as a consultant for public local authorities in the company Ressources Consultants Finances. I started working in the field of Proteomics in October 2014 in the EDyP laboratory located in Grenoble (http://www.edyp.fr/). I have been working on the improvement of statistical analysis of bottom-up proteomics data. Today, most of the projects I work on consist of detecting changes in protein abundances using discovery-driven mass spectrometry. I am interested in the development of new methodologies to optimize proteomics data analysis pipelines, from the identification of peptides/proteins to their quantification and the interpretation of results. For this purpose, I worked on several R packages which can be downloaded from the CRAN and Bioconductor: cp4p (https://cran.r-project.org/web/packages/cp4p/index.html), imp4p (https://cran.r-project.org/web/packages/imp4p/index.html), DAPAR (http://bioconductor.org/packages/release/bioc/html/DAPAR.html) and its GUI ProStar.
Machine learningModelingPathway AnalysisProteomicsStatistical inferenceBiostatisticsApplication of mathematics in sciencesData and text miningData integrationStatistical experiment designMultidimensional data analysis
Data VisualizationMachine learningStatistical inferenceBiostatisticsApplication of mathematics in sciencesDimensional reductionMultidimensional data analysis
- Optimisation of freeze and conservation method of peripherical blood mononucleated cells(SORDOILLET VALLIER - Other) - Pending
- Afribiota-Neuro(Pascale VONAESCH - Molecular Microbial Pathogenesis) - In Progress
- Genetic and statistical analysis of data produced with the Collaborative Cross at the Institut Pasteur(Xavier MONTAGUTELLI - Mouse Genetics) - In Progress
Bernd Jagla received his PhD in bioinformatics (department of Biology, Chemistry, and Parmacy) from the Free University in Berlin, Germany in 1999. Before joining the Institut Pasteur, he worked for almost ten years in New York City, including as an associate research scientist in the Joint Centers for System Biology (Columbia University) and at the Columbia University Screening Center led by Dr J.E. Rothman. He joined the Institut Pasteur in 2009 to take charge of the bioinformatic needs at the Transcriptome et Epigenome platform, focusing on Next Generation Sequencing. As of 2016 he is member of the C3BI – HUB Team detached to the Human immunology center (CIH) and provides support for cytometry, next generation sequencing, and microarray data analysis. His areas of interest include the quality assurance and data analysis and visualization at the facility. He also has strong expertise in developing algorithms for function prediction from sequence data, image analysis, analysis of mass spectrometry data, workflow management systems. While at Pasteur he developed: KNIME extensions for Next Generation Sequencing (Link) Post Alignment Visualization and Characterization of High-Throughput Sequencing Experiments (Link) Post Alignment statistics of Illumina reads (Link)
AlgorithmicsChIP-seqData managementData VisualizationImage analysisMachine learningSequence analysisDatabaseGenome analysisBiostatisticsProgram developmentScientific computingData and text miningIllumina HiSeqGraphics and Image ProcessingIllumina MiSeqHigh Throughput ScreeningFlow cytometry/cell sortingPac Bio
Image analysisStatistical inferenceBiostatisticsGeneticsSequencingDiagnostic tools
- Serpentine: a flexible 2D binning method for differential Hi-C analysis(Vittore SCOLARI - Spatial Regulation of Genomes) - In Progress
- The anti-IgE antibody Omalizumab induces adverse reactions through engagement of Fc gamma receptors(Bianca BALBINO - Antibodies in Therapy and Pathology) - In Progress
- LGP2 binds PACT to regulate RIG-I- and MDA5-mediated antiviral response(Anastassia KOMAROVA - Viral Genomics and Vaccination) - In Progress
Thomas is a biostatistician who holds an engineering degree in Agronomy (Agrocampus Ouest, Rennes, France). He also holds a Ph.D. in biostatistics from Université Pierre et Marie Curie for his work on the spread of nosocomial pathogens on contact networks. During his Ph.D at INSERM, he investigated how high-resolution dynamical contact data could support infection-tracing conducted using more traditional approaches in healthcare settings, e.g. routine swabbing and genetic characterization of strains detected in patients or healthcare workers. He developed a new statistical framework to test the correlation between dynamic close-proximity interaction networks and biological carriage data. While at INSERM, he also developed the R0 package for R that aimed at implementing several computation methods used in estimating reproduction parameters for emerging transmissible diseases. After working as a statistical modeller for a private company in the pharmaceutical industry, he joined the Hub in 2016 as a statistician and is now involved in the projects of the Malaria: parasites and hosts unit headed by Ivo Mueller.
ModelingBiostatisticsScientific computingApplication of mathematics in sciencesClinical researchEpidemiology and public health
- Impact des contraintes biomécanistiques sur la dynamique des macro-ouverture induits par l'EDIN de Staphylococcus aureus.(Camille MOREL - Bacterial Toxins) - In Progress
- An Aedes albopictus-driven epidemiological prediction for arboviral diseases outbreak in Europe(Pei-Shi YEN - Arboviruses and Insect Vectors) - Pending
- Evaluation de la représentativité génétique d'un pool de souches(Emilie SITTERLÉ - Fungal Biology and Pathogenicity) - In Progress
Since February 2017 Research engineer, Hub of Bioinformatics and Biostatistics of the C3BI, Institut Pasteur 2015-2017 Post doctoral position, team MISTIS, INRIA Grenoble Topic: Robust clustering and robust non linear regression in high dimension. Collaboration with Florence Forbes (INRIA). 2012-2015 PhD thesis in Statistics, Applied Mathematics Department of Agrocampus-Ouest, IRMAR UMR 6625 CNRS, Rennes Topic: Stability of variable selection in regression and classification issues for correlated data in high dimension. Supervisor: David Causeur (Agrocampus-Ouest, IRMAR). Education 2015 PhD thesis in Statistics, Applied Mathematics Department of Agrocampus-Ouest, IRMAR UMR 6625 CNRS, Rennes 2012 ISUP degree (Institut de Statistique de l’UPMC), Université Pierre et Marie Curie, Paris 2012 Master 2 of Statistics, Université Pierre et Marie Curie, Paris
ClusteringModelingStatistical inferenceTranscriptomicsBiostatisticsExploratory data analysisDimensional reductionStatistical experiment designMultidimensional data analysis
- Analysis of the clinical manifestations of Lyme borreliosis in France from 2003 to 2011(Valerie CHOUMET - Environment and Infectious Risks) - In Progress
- Distribution of Cytotoxic necrotizing factor 1 among the sequence type 131 emergent multidrug resistant lineage of Escherichia coli(TSOUMTSA MEDA LANDRY LAURE - Bacterial Toxins) - In Progress
- Quality controls for human plasmas and serums stored in biobanks(HELENE LAUDE - Biological Resource Center of Institut Pasteur (CRBIP)) - In Progress
Dr. Natalia Pietrosemoli is an Engineer with a M. Sc. in Modeling and Simulation of Complex Realities from the International Center for Theoretical Physics, ICTP and the International School of Advanced Studies, SISSA (Triest, Italy). During her M. Sc. internships she mostly worked in modeling, optimization, combinatorics and information theory applied to medical imaging. In 2012 she got a Ph. D in Computational Biology from the School of Bioengineering of Rice University (Houston, TX, US), where she specialized in computational structural biology and functional genomics. Her doctoral thesis “Protein functional features extracted with from primary sequences : a focus on disordered regions”, contributed to a better understanding of the functional and evolutionary role of intrinsic disorder in protein plasticity, complexity and adaptation to stress conditions. As part of her Ph. D., Natalia was a visiting scholar in two labs in Madrid: the Structural Computational Biology Group at the Spanish National Cancer Research Centre (CNIO), where she mainly worked in sequence analysis and the functional-structural relationships of proteins, and the Computational Systems Biology Group at the Spanish National Centre for Biotechnology (CNB-CSIC ), where she studied the functional implications of intrinsically disordered proteins at the genomic level for several organisms, collaborating with different experimental and theoretical groups. In 2013, she joined the Swiss Institute of Bioinformatics as a postdoctoral fellow in the Bioinformactics Core Facility. Her main project consisted in the molecular classification of a rare type of lymphoma, which involved the integration of transcriptomic, clinical and mutational data for the identification of molecular markers for classification, diagnosis and prognosis. This work was performed in collaboration with the Pathology Institute at the University Hospital of Lausanne (CHUV). In November of 2015 Natalia joined the Hub Team @ Pasteur C3BI as a Senior Bioinformatician. Natalia is especially interested in the integrative analysis of different omics data, both at large-scale and for small datasets, and loves collaborating in interdisciplinary environments and having feedback from her fellow experimental colleagues. Currently, she’s coordinating several projects performing functional and pathway analysis at the genomic level. By grouping genes, proteins and other biological molecules into the pathways they are involved in, the complexity of the analyses is significantly reduced, while the explanatory power increases with respect to having a list of differentially expressed genes or proteins.
AlgorithmicsData managementGenomicsImage analysisMachine learningModelingProteomicsSequence analysisStructural bioinformaticsTranscriptomicsDatabaseGenome analysisBiostatisticsScientific computingDatabases and ontologiesApplication of mathematics in sciencesData and text miningGeneticsGraphics and Image ProcessingBiosensors and biomarkersClinical researchCell biology and developmental biologyInteractomicsBioimage analysis
- Determination of the transcriptome controlled by the two-component system BvrR/BvrS using dominant positive and negative BvrR mutants(Javier PIZARRO-CERDA - Yersinia) - Pending
- Analyse transcriptionnelle du cellules cancéreuse intestinal vs normales après co-culture avec la bactérie associée au cancer Streptococcus gallolyticus(Ewa PASQUEREAU - Biology of Gram-Positive Pathogens) - Pending
- Functional interactomics of SKAP2(Jean-François BUREAU - Functional Genetics of Infectious Diseases) - Pending
Hugo Varet is a biostatistician engineer from the Ensai (Ecole Nationale de la Statistique et de l’Analyse de l’Information) and has been recruited by the hub of the C3BI (Center of Bioinformatics, Biostatistics and Integrative Biology) to work at the Transcriptome & Epigenome Platform. He is in charge of the statistical analyses of the RNA-Seq data produced by the platform and develops R pipelines that help in this task. One of them is named SARTools and is available on GitHub: https://github.com/PF2-pasteur-fr/SARTools.
ModelingSequence analysisStatistical inferenceTranscriptomicsBiostatisticsScientific computingApplication of mathematics in sciencesExploratory data analysisHigh Throughput ScreeningClinical research
- Antiviral activities of anti-HIV-1 antibodies(Timothée BRUEL - Virus and Immunity) - Pending
- Defining Shigella-targeting of human lamina propria mononuclear cells using CyTOF technology(Katja BRUNNER - Molecular Microbial Pathogenesis) - Closed
- Exploring immunological mechanisms of human graft-verus-host disease after hematopoietic stem cell transplantation(Eleonora LATIS - Immunoregulation) - Closed
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 (18)
Insight into the Immune System: A bioresource and data-sharing platform to study chronic inflammatory diseases (IsIShare)
Chronic inflammatory systemic diseases (CIDs) are a burden to humans because of life-long debilitating illness, increased mortality and high therapy costs. CIDs’ increasing prevalence in western countries has indeed placed them at the third rank of morbi-mortality causes. Unfortunately, available treatments are poorly targeted and non-curative. That is partly linked to a complex and largely ununderstood pathophysiology. Genetic susceptibility clearly plays a role. Genes linked to the immune system have been identified, but causal genes remain mostly unknown and other factors such as intestinal microbiota have also been implicated. The complexity of CIDs’ pathophysiology suggests that a holistic approach is the most susceptible to help make significant progress. Our project intends to take advantage of recent technical progress and development of informatics tools to set up a transversal approach. High-resolution sequencing technology indeed quickly produces large amounts of accurate data. Besides, new integrative informatics tools allowing storage and integrative analysis of this resulting high amount of data are now available. We intend to set-up a CID’s network allowing the gathering and extensive analysis of data related to immuno-genetic determinants, immune repertoire and microbiota from individuals suffering from one of the three major interlinked CIDs, namely Hidradenitis Suppurativa (HS), Crohn’s disease (CD) and Spondyloarthropathy (SpA) as compared to healthy volunteers.
It has been shown that methylation can act as a kind of memory of the immune system. For patients with co-infections, it is of particular importance to know when to begin an anti-retroviral therapy, especially if they are already infected with tuberculosis. The goal of this study is to find hyper or hypo methylated loci related to the reaction of HIV patients (co-infected or not) to different kind of treatments.
Genetic traits involved in the regulation of NK cell and ILC homeostasis and NK cell-mediated anti-tumor functions
This project aims at identifying novel genetic traits that regulate the anti-tumor activities of NK cells and homeostasis of NK cells and other ILC using an unique mouse resource, the Collaborative Cross (CC). CC is a panel of recombinant inbred mice derived from randomized breeding of eight laboratory inbred strains combining high genetic diversity with the advantage of inbred mouse strains. We have identified CC strains that diverge in their anti-tumor immune responses and are characterizing the molecular mechanisms responsible for these differences. Ultimately, these diverse genetic traits may lead to the development of novel therapies for cancer.
Taking advantage of a murine model of controlled microbiota composed of 12 strains, we evaluated the activity of a cocktail of three virulent bacteriophages to target a murine Escherichia coli strain
In this project we study ecological diversification of Klebsiella pneumoniae and closely related species. Using comparative genomics we want to identify the pattern of genome adaptation to different e
Identification of immune response signatures that correlate with therapeutic responses to TNF inhibitors using machine-learning algorithms
Anti-TNF therapy has revolutionized treatment of many chronic inflammatory diseases, including rheumatoid arthritis, Crohn’s disease and spondyloarthritis (SpA). However, clinical efficacy of TNF-inhi
Mitochondria are double-membrane bound organelles that are essential in every tissue of the body. They are metabolic hubs and signalling platforms that are deeply integrated into cellular homeostasis.
Our goal is to have a bioinformatic tool that performs the 2 x 2 comparison of matrices of numbers in matrix batches. Each matrix corresponds to the use of gene fragments (V or J) to create a re-arran
Asymptomatic pathogen carriage in stunted and non-stunted children living in Antananarivo, Madagascar
This project is integrated in the analysis of the gut ecosystem of children implicated in the AFRIBIOTA project, a translational project performed within a consortium of researchers and medical doctor
Impact des contraintes biomécanistiques sur la dynamique des macro-ouverture induits par l'EDIN de Staphylococcus aureus.
Several bacterial pathogens compromise the barrier function of endothelia by triggering the opening of transendothelial cell macroaperture (TEM) tunnels as large as several micrometres in width. This
Globally one out of four children under 5 years is affected by linear growth delay (stunting). This syndrome has severe long-term sequelae including increased risk of illness and mortality and delayed
We need an independent statistician to confirm that appropriate statistical tests were used to analyze the data in your manuscript for the final revision of our manuscript in Science Signaling (Manus
Without new treatment development tuberculosis could cause about 70 million deaths by 2050, mostly due to the spread of multidrug-resistant strains. The standard drug regimen still builds on the first
Complex chronic diseases are caused by the accumulation of genetic, microbial and lifestyle factors. The number and complexity of such factors makes prediction of pathogenesis and therapy particularly
The provision of human biological material collected, processed and stored under optimal conditions is crucial to ensure the quality of research carried out downstream. These optimal conditions must b
The therapeutic anti-IgE antibody Omalizumab is used for the treatment of severe asthma, and is known to trigger anaphylaxis in some patients. Since Omalizumab is a humanized IgG1, so we hypothesized
Hi-C contact maps reflect the relative contact frequencies between pairs of genomic loci, quantified through deep-sequencing. Differential analyses of these maps facilitate downstre
Epidemiological data report an association between obesity and inflammatory bowel disease (IBD). Furthermore, animal models demonstrate that maternal high fat diet (HFD) and maternal obesity increase