Abstract
The open analytics platform KNIME is a modular environment that enables easy visual assembly and interactive execution of workflows. KNIME is already widely used in various areas of research, for instance in cheminformatics or classical data analysis. In this tutorial the KNIME Image Processing Extension is introduced, which adds the capabilities to process and analyse huge amounts of images. In combination with other KNIME extensions, KNIME Image Processing opens up new possibilities for inter-domain analysis of image data in an understandable and reproducible way.
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The entire Phenotype Classification workflow is available for download at http://knime.imagej.net/aaec.
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For detailed information see http://www.broadinstitute.org/bbbc/BBBC013/. Please note: The BMP images available on the website are already split into the individual channels.
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For details and installation instructions see https://tech.knime.org/community/imagej.
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For details see the example workflows on http://tech.knime.org/supervised-image-segmentation.
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For details see Phenotype Classification workflow at http://knime.imagej.net/aaec.
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see http://www.broadinstitute.org/bbbc/BBBC013/ for details on the plate design.
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Dietz, C., Berthold, M.R. (2016). KNIME for Open-Source Bioimage Analysis: A Tutorial. In: De Vos, W., Munck, S., Timmermans, JP. (eds) Focus on Bio-Image Informatics. Advances in Anatomy, Embryology and Cell Biology, vol 219. Springer, Cham. https://doi.org/10.1007/978-3-319-28549-8_7
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