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Mikhail Chernykh, Yannis Kalaidzidis, Giovanni Marsico, Claudio Collinet, Nikolay Samusik, Thierry Galvez, Marino Zerial (Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany)
Visualization of complex multidimensional data is a challenging task. Our aim was to create quantitative profiles of the activity of human genes with respect to Transferrin (Tfn) and Epidermal Growth Factor (EGF) endocytosis using data utilizing the combination of genome-wide RNAi, automated high-resolution confocal microscopy, quantitative multiparametric image analysis and high-performance computing. The results of these profiles were summarised in a database. We developed an interactive mechanism to visually represent, compare and query the gene and siRNA profiles. This visualisation technique facilitates the understanding and mining of the screen data. The architecture of our web-database is highly adaptable and will be used further for a wide range of multiparametric assays with an extended number of parameters currently on-going in our lab. The database is publicly available at http://endosomics.mpi-cbg.de/.