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  • KNIME: Practical introduction to KNIME Analytics platform and its application in bioinformatics (Webinar)

    29 - 30 July 2020

    Cambridge, United Kingdom

    Elixir node event
    KNIME: Practical introduction to KNIME Analytics platform and its application in bioinformatics (Webinar) https://tess.elixir-europe.org/events/knime-practical-introduction-to-knime-analytics-platform-and-its-application-in-bioinformatics-webinar This event introduces participants to the [KNIME](https://www.knime.com/) Analytics Platform, an open source data science platform with a visual workflow editor, that can be used by users without prior programming experience or integrated with existing scripts written in R or Python. These sessions are aimed towards anyone who has an interest in building data science workflows with different kinds of life science data. The sessions will cover how to aggregate data from different sources (e.g., files, databases, web services), how to calculate simple statistics (e.g., for data exploration), network mining (e.g., protein-protein interactions) and big data analytics (e.g., next-generation sequencing data). The webinar will combine practical and taught content to demonstrate how users can use KNIME to design and utilise reproducible data science workflows, such as analytics tasks, and better explore and understand their data. 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=3508000&amp;course-title=KNIME%20webinar).'' 2020-07-29 13:00:00 UTC 2020-07-30 15:00:00 UTC University of Cambridge Craik-Marshall Building, Cambridge, United Kingdom Craik-Marshall Building Cambridge United Kingdom CB2 3AR Data visualisation Bioinformatics University of Cambridge Bioinformatics Training [] This hands-on event is suitable for anyone who has an interest in building data science workflows with different kinds of life science data.Graduate studentsPostdocs and Staff members from the University of CambridgeInstitutions and other external Institutions or individuals<span style="color:#FF0000">There is no fee charged for this event''<span style="color:#FF0000"> workshops_and_courses [] HDRUK

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