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 : Application of mathematics in sciences
Related people (10)
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 have a joint MSc degree in Mathematical Modelling from three European universities: University of L’Aquila (Italy), University of Nice-Sophia Antipolis (France) and Autonomous University of Barcelona (Spain). I also hold a PhD degree in Applied Mathematics and Scientific Computing from University of Bordeaux, France. I have done my PhD and one year of post-doc at INRIA Bordeaux Sud-Ouest, and partially at IHU-Liryc. During this time I studied how electrical signals propagate through the cardiac tissue under certain diseased conditions. My model of interest was the bidomain model, which is a system of partial differential equations that takes into account physiological properties of the cardiac cells and the spatial organization of the cardiac tissue. I worked on the mathematical multiscale analysis and numerical simulations of the problem to understand how structural changes of the tissue affect the propagation of the signal on the heart level. I collaborated with biologists and engineers of the IHU-Liryc to apply my model on a rat heart using high-resolution MRI data. For this I also worked on image analysis and image processing. I’ve joined the Institute Pasteur in February 2018 as a member of the HUB in Bioinformatics and Biostatistics. Currently I am working on stochastic mathematical modeling and inference for systems biology, gene expression, RNA transcription, etc.
ModelingScientific computingApplication of mathematics in sciencesGraphics and Image Processing
BacteriaFungiInsect or arthropodEscherichia coliSaccharomyces cerevisiaeFly
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) - Awaiting Publication
- 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
Data VisualizationMachine learningStatistical inferenceBiostatisticsApplication of mathematics in sciencesDimensional reductionMultidimensional data analysis
- Coaching in R(Elisabetta BIANCHI - Immunoregulation) - In Progress
- Collaboration between CETEA, C2RA and Hub for optimization of experimental designs (3R)(Myriam MATTEI - Center for Animal Resources and Research) - In Progress
- Assessing the role of gut microbiota in spondyloarthritis patients and impact of anti-TNF treament on its composition(Corinne RICHARD-MICELI - Immunoregulation) - Closed
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) - Closed
- Evaluation de la représentativité génétique d'un pool de souches(Emilie SITTERLÉ - Fungal Biology and Pathogenicity) - 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
- Mitochondrial polarization identifies functionally mature human NK cells(Laura SURACE - Innate Immunity) - In Progress
- Proteomic analysis of the intracellular compartments containing Brucella abortus(Javier PIZARRO-CERDA - Yersinia) - In Progress
- Secretome Analysis of OIS IL6KO SASP(Mathieu VON JOEST - Cellular Plasticity And Disease Modelling) - In Progress
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 in 2013 by the Transcriptome & Epigenome Platform of the Biomics Pole. Late 2014 he obtained a permanent position at the Bioinformatics & Biostatistics Hub and has been detached to the platform to continue the statistical analyses of RNA-Seq data and develop R pipelines and Shiny applications that help in this task. One of them is named SARTools and is available on GitHub: https://github.com/PF2-pasteur-fr/SARTools. In December 2019 he left the Biomics Platform and joined the Bioinformatics & Biostatistics Hub as a core-member.
ModelingSequence analysisStatistical inferenceTranscriptomicsBiostatisticsScientific computingApplication of mathematics in sciencesExploratory data analysisHigh Throughput ScreeningClinical research
- Effect of metabolic disturbance on the host transcriptional profile during Chlamydia infection(Agathe SUBTIL - Cellular Biology of Microbial Infection) - Pending
- Correlative analysis between lipid droplets number and volume in hepatocytes infected by hepatitis C virus variants(Emeline SIMON - Molecular Genetics of RNA Viruses) - Closed
- Analysis of the transcriptome during lyssavirus infection in torpid bat: an in vitro model. Act 1(Laurent DACHEUX - Lyssavirus Dynamics and Host Adaptation) - Pending
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
- Development and design of new functionalities for MEMHDX, a web application dedicated to the statistical analysis and vizualization of large HDX-MS datasets.(Sebastien BRIER - Biological NMR Technological Platform) - In Progress
- Optimisation of freeze and conservation method of peripherical blood mononucleated cells(SORDOILLET VALLIER - Other) - Pending
- Hamper cell-to-cell variation to enhance drug-mediated killing(Giulia MANINA - Microbial Individuality and Infection) - Pending
A computer scientist by training, I am applying this knowledge to solve biological problems and am particularly interested in modelling of biological systems, knowledge inference, ontologies and data visualisation.
AlgorithmicsData VisualizationMetabolomicsModelingPathway AnalysisPhylogeneticsSystems BiologyTool DevelopmentDatabaseProgram developmentScientific computingDatabases and ontologiesApplication of mathematics in sciencesSofware development and engineeringData and text miningEvolutionData integrationGraph theory and analysisWorkflow and pipeline developmentDiscrete and numerical optimization
VirusHuman Immunodeficiency virus (HIV)
- Modeling mitochondrial metabolism dormant Cryptococcus neoformans(Benjamin HOMMEL - Molecular Mycology) - Closed
- Measles virus protein C interplay with cellular apoptotic pathways; applications for cancer treatment(Alice MEIGNIÉ - Viral Genomics and Vaccination) - Closed
- Diffusion des mutations de résistance du VIH : modèles et méthodes d’estimation(Olivier GASCUEL - Evolutionary Bioinformatics) - In Progress