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 : Image analysis

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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 (2)


Group : DETACHED - Hub Core

Image reconstruction, processing and analysis. Dingle molecule localization microscopy. Development of ImageJ and Fiji plugins.

Image analysisGraphics and Image Processing

Projects (0)


    Group : SysBio - 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 (32)

    Related projects (2)

    High content screening of mitochondrial morphology defects in mitochondrial genetic diseases

    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. The functions of mitochondria are intimately linked to their form, which is regulated by a balance of membrane fusion and fission: dynamin-like GTPases OPA1 and MFN1/2 perform membrane fusion and DRP1 regulates membrane fission. Mutations in mitochondrial genes cause a pleiotropic spectrum of clinical disorders whose underlying genetic, morphological and biochemical defects can be easily studied in skin fibroblasts generated from patient biopsies. The morphology of mitochondria is inextricably linked to its many essential functions in the cell and we are interested in understanding the relationship between mitochondrial shape changes and metabolism in the context of acquired and inborn human diseases. Balanced fusion and fission events shape mitochondria to meet metabolic demands and to ensure removal of damaged organelles. Mitochondrial fragmentation occurs in response to nutrient excess and cellular dysfunction and has been observed in mitochondrial genetic diseases and is thought to play an important role in the development of disease. The physiological relevance of mitochondrial morphology and the mechanisms that regulate mitochondrial dynamics are incomplete and so we have set out to find ways to rebalance mitochondrial dynamics in genetic diseases. We recently developed imaging and informatics pipelines to allow for the automated, rapid, reliable quantification of mitochondrial morphology in human fibroblasts. We applied this new technology in the context of genome-wide siRNA screens in immortalized fibroblasts from an OPA1 patient with dominant optic atrophy and control fibroblasts to identify candidate genes able to reverse the mitochondrial fragmentation phenotype associated with mitochondrial dysfunction in patient cells. We have performed the same genome-wide screen in healthy immortalized control fibroblasts. Together, these studies will help us identify lists of genetic modifiers and therapeutic targets that can be investigated further using cell biology and biochemical tools in the lab.

    Project status : Closed

    An integrated software having a graphical user interface for the analysis of time-lapse images of bacterial microcolonies

    Project status : Closed