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 : Modeling
Related people (11)
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
I received a Ph.D. in Biostatistics and Bioinformatics applied to Cancer Research in 2011 from the University Paris Sud XI, I was working at the Curie institute under the supervision of Emmanuel Barillot and François Radvanyi. My Ph.D. was about the unsupervised analysis of cancer transcriptome. During my postdoctoral time, I worked on the computational and statistical analysis of NGS data. My areas of interest and expertise include - functional genomics - human genetics - statistical analysis of high-dimensional data - normalization, batch-correction, meta-analysis of high-throughput data - unsupervised learning, independent component analysis - NGS data analysis (RNA-Seq, DNA-Seq, …) - analysis of the non-coding genome, transposable elements
- Mechanisms of HIV-1-infected cells susceptibility to Fc effector functions(Timothée BRUEL - Virus and Immunity) - In Progress
- Characterization of Yolk Sac Derived Progenitors in the Fetal Liver(Laina FREYER - Macrophages and Endothelial Cells) - Pending
- Gene expression and its regulation during and after inpatient detoxification of cocaine: a link to relapse?(Romain ICICK - Integrative Neurobiology of Cholinergic Systems) - In Progress
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
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
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
- Assessing the role of gut microbiota in spondyloarthritis patients and impact of anti-TNF treament on its composition(Corinne RICHARD-MICELI - Immunoregulation) - Pending
- Uncovering diversity and improving gene annotation of Leptospira sppo(Mathieu PICARDEAU - Biology of Spirochetes) - Pending
- Characterization of the bacterial and fungal microbiota in Aedes aegypti natural breeding sites and larvae(Louis LAMBRECHTS - Insect-Virus Interactions) - Pending
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
- Spatial analysis of cysticercosis seroprevalence in villages of Ivory Coast(RONAN JAMBOU - Department of Infection & Epidemiology) - Pending
- Role of Tunneling nanotubes in Glioblastoma(Giulia PINTO - Membrane Traffic and Pathogenesis) - In Progress
- Analysis of the clinical manifestations of Lyme borreliosis in France from 2003 to 2011(Valerie CHOUMET - Environment and Infectious Risks) - 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
- Proteomic analysis of the intracellular compartments containing Brucella abortus(Javier PIZARRO-CERDA - Yersinia) - Pending
- Secretome Analysis of OIS IL6KO SASP(Mathieu VON JOEST - Cellular Plasticity And Disease Modelling) - Pending
- Microscystis transcriptome(Muriel GUGGER - Collection of Cyanobacteria) - 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) - Closed
- 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
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) - In Progress
- Measles virus protein C interplay with cellular apoptotic pathways; applications for cancer treatment(Alice MEIGNIÉ - Viral Genomics and Vaccination) - In Progress
- Diffusion des mutations de résistance du VIH : modèles et méthodes d’estimation(Olivier GASCUEL - Evolutionary Bioinformatics) - In Progress
Related projects (4)
Lyme borreliosis is the most common tick-borne disease in the northern hemisphere. In Europe, it is transmitted by Ixodes ticks that carries bacteria belonging to the Borrelia burgdorferi sensu lato complex. Our study was focused on peri-urban forests of Île-de-France. These forests are frequented by many visitors and the risk of exposure to tick bites is high. One of them, the Sénart forest, is located 30 km south of Paris (in the Île-de-France region) and has a large number of visitors (3 million per year in the late 1990s). This forest has the characteristics of being partly invaded by chipmunks (Tamias sibiricus). The chipmunk has been introduced from Eurasia, particularly Siberia, China and Korea. The first individuals were released by their owners at the western end of the Sénart forest, in the 1970s. The northeastern part of the forest was colonized recently. Our current study aims to evaluate the evolution of the infection of Ixodes ricinus by Borrelia burgdorferi sl. by comparing the results obtained during 3 years and to determine the consequences of the proliferation of this non-native rodent species, Tamias sibiricus, on the risk of transmission of Lyme borreliosis. For this purpose, we analyzed the rate of infection and the density of infected ticks during 2008, 2009 and 2011 in several locations of the Sénart forest. These results were compared to those obtained for ticks collected in 2009 in two other peri-urban forests of Île-de-France (Rambouillet and Notre-Dame) that have not yet been colonized by these rodents. The density of nymphs, adults as well as the infected density of nymphs and adults were compared according to several factors: location of tick collection in the forest, presence or absence of chipmunks, type of vegetation, temperature and humidity.
Quantitatively understanding the stochastic dynamics of gene expression requires measurements at the level of single cells. A common approach to follow the expression of genes in single cells and in real time is to make use of fluorescent reporter proteins and to record the cells' fluorescence by microscopy. However, this provides only an indirect readout of the biological processes that are of interest such as the regulation mechanisms at the promoter. A possible way to uncover the unobservable biological processes is to infer the hidden dynamics from the available data through the use of mechanistic models of gene expression. The goal of this project is to develop methods for state estimation and parameter inference for such models and to test these methods on real data.
In early development, regulation of transcription results in precisely positioned and highly reproducible expression patterns that specify cellular identities. How transcription, a fundamentally noisy
Cellular senescence is a complex stress response that durable (yet not irreversibly) arrests cell proliferation and is accompanied by widespread changes in chromatin structure, metabolism and gene exp