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 : Data and text mining

Related people (9)


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

Projects (0)

    Thomas COKELAER

    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)

    Amine GHOZLANE

    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)


    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 ( 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 (, imp4p (, DAPAR ( and its GUI ProStar.

    Machine learningModelingPathway AnalysisProteomicsStatistical inferenceBiostatisticsApplication of mathematics in sciencesData and text miningData integrationStatistical experiment designMultidimensional data analysis
    Non applicable
    Projects (1)

    Bernd JAGLA

    Group : PLATEFORM - Detached : Biomarker Discovery

    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

    Projects (1)

    Christophe MALABAT

    Group : HEAD - Hub Core

    After a PhD in biochemistry of the rapeseed proteins, during which I developed my first automated scripts for handling data processing and analysis, I join Danone research facility center for developing multivariate models for the prediction of milk protein composition using infrared spectrometry.
    As I was already developing my own informatics tools, I decided to join the course of informatic for biology of the Institut Pasteur in 2007. At the end of the course I was recruited by the Institute and integrate the unit of “génétique des interactions macromoléculaires” of Alain Jacquier. Within this group, I learn to handle sequencing data and I developed processing and analysis tools using python and R. I also create a genome browser and database system for storing, retrieving and visualizing microarray data. After 8 years within the Alain Jacquier’s lab, I join the Hub of bioinformatics and biostatistics as co-head of the team.

    ClusteringData managementSequence analysisTranscriptomicsWeb developmentDatabaseGenome analysisProgram developmentScientific computingExploratory data analysisData and text miningIllumina HiSeqRead mappingLIMSIllumina MiSeqHigh Throughput ScreeningMultidimensional data analysisWorkflow and pipeline developmentRibosome profilingMotifs and patterns detection

    Projects (9)


    Group : FUNGEN - Hub Core

    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

    Projects (25)