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 : Clinical research
Related people (3)
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
- Mosquito vector competence for Zika virus(Anna-Bella FAILLOUX - Arboviruses and Insect Vectors) - Pending
- Tests serologics anti-CNF1(Daniel GUERIN - Bacterial Toxins) - In Progress
- Impact des contraintes biomécanistiques sur la dynamique des macro-ouverture induits par l'EDIN de Staphylococcus aureus.(Camille MOREL - Bacterial Toxins) - 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
- Global BioID-based SARS-CoV-2 proteins proximal interactome unveils novel ties between viral polypeptides and host factors involved in multiple COVID19-associated mechanisms(Yves JACOB - Molecular Genetics of RNA Viruses) - In Progress
- Mitochondrial polarization identifies functionally mature human NK cells(Laura SURACE - Innate Immunity) - Awaiting Publication
- Proteomic analysis of the intracellular compartments containing Brucella abortus(Javier PIZARRO-CERDA - Yersinia) - 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.
MetabolomicsModelingSequence analysisStatistical inferenceTranscriptomicsBiostatisticsScientific computingApplication of mathematics in sciencesExploratory data analysisHigh Throughput ScreeningClinical research
- Transcriptional analysis of injured skeletal muscle(Eleonora ROSSI - Stroma, Inflammation and Tissue Repair) - Closed
- 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) - In Progress