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  • Mouse Genome Informatics workshop

    27 October 2015

    Cambridge, United Kingdom

    Elixir node event
    Mouse Genome Informatics workshop https://tess.elixir-europe.org/events/mouse-genome-informatics-workshop-579098c1-61f1-486d-9df2-c1cec673442e [Mouse Genome Informatics (MGI)](http://www.informatics.jax.org) is the international database resource for the laboratory mouse and provides integrated genetic, genomic, and biological data to facilitate the study of human health and disease. MGI is a free, highly curated resource and offers web and programmatic access to a complete catalogue of mouse genes and genome features, functional annotations, a comprehensive catalogue of mutant and knockout alleles, phenotype and human disease model annotations, gene expression, variation and sequence data. This workshop will be composed of ~20min overview and ~1 hour hands-on, interactive tutorial. Please note that if you are not eligible for a University of Cambridge [Raven](http://www.ucs.cam.ac.uk/docs/faq/raven/n5) account you will need to book by linking [here](http://marstons.bio.cam.ac.uk/course-booking/?CourseID=Mouse%20Genome%20Informatics%20workshop_bioinfo-mgi_27.10.2015_1541354&CourseName=Mouse%20Genome%20Informatics%20workshop&CourseDate=27.10.2015&CourseDuration=0.5&EventID=1541354).'' 2015-10-27 10:00:00 UTC 2015-10-27 12:00:00 UTC University of Cambridge Craik-Marshall Building, Cambridge, United Kingdom Craik-Marshall Building Cambridge United Kingdom CB2 3AR University of Cambridge Bioinformatics Training [] other model organisms studies human diseases or developmental biology Postdocs and Staff members from the University of Cambridge Institutions and other external Institutions or individuals workshops_and_courses [] []
  • Biological Imaging Data Processing for Data Scientists

    8 December 2017

    Cambridge, United Kingdom

    Elixir node event
    Biological Imaging Data Processing for Data Scientists https://tess.elixir-europe.org/events/biological-imaging-data-processing-for-data-scientists [The Open Microscopy Environment](https://www.openmicroscopy.org/) (OME) is an open-source software project that develops tools that enable access, analysis, visualization, sharing and publication of biological image data. OME has three components: * OME-TIFF, standardised file format and data model; * Bio-Formats, a software library for reading proprietary image file formats; and * OMERO, a software platform for image data management and analysis. In this one day course, we will present the OMERO platform, and show how to transition from manual data processing to automated processing workflows. We will introduce how to write applications against the OMERO API, how to integrate a variety of processing tools with OMERO and how to automatically generate output ready for publication. This course is organized alongside a one day course on Biological Imaging Data Management for Life Scientists. More information on this event are available [here](https://training.csx.cam.ac.uk/bioinformatics/event/2239247). This course will be delivered by members of the OMERO team. The OME project is supported by BBSRC and Wellcome Trust. Please note that if you are not eligible for a University of Cambridge [Raven](http://www.ucs.cam.ac.uk/docs/faq/raven/n5) account you will need to book or register your interest by linking [here](http://bioinfotraining.bio.cam.ac.uk/booking-form/?event-id=2280783&course-title=Biological%20imaging%20data%20management%20for%20data%20scientists).'' 2017-12-08 09:30:00 UTC 2017-12-08 17:00:00 UTC University of Cambridge Craik-Marshall Building, Cambridge, United Kingdom Craik-Marshall Building Cambridge United Kingdom CB2 3AR Data management Biological imaging Bioinformatics University of Cambridge Bioinformatics Training [] Life scientists with programming skillsbioinformaticians and image analysts.Anybody interested in using Jupyter and OMEROGraduate studentsPostdocs and Staff members from the University of CambridgeInstitutions and other external Institutions or individuals workshops_and_courses [] HDRUK
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