Abstract
High-content screening (HCS) has established itself in the world of the pharmaceutical industry as an essential tool for drug discovery and drug development. HCS is currently starting to enter the academic world and might become a widely used technology. Given the diversity of problems tackled in academic research, HCS could experience some profound changes in the future, mainly with more imaging modalities and smart microscopes being developed. One of the limitations in the establishment of HCS in academia is flexibility and cost. Flexibility is important to be able to adapt the HCS setup to accommodate the multiple different assays typical of academia. Many cost factors cannot be avoided, but the costs of the software packages necessary to analyze large datasets can be reduced by using open-source software. We present and discuss the open-source software CellProfiler for image analysis and KNIME for data analysis and data mining that provide software solutions, which increase flexibility and keep costs low.
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This work was supported by the Max Planck Gesellschaft.
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Stöter, M., Janosch, A., Barsacchi, R., Bickle, M. (2019). CellProfiler and KNIME: Open-Source Tools for High-Content Screening. In: Moll, J., Carotta, S. (eds) Target Identification and Validation in Drug Discovery. Methods in Molecular Biology, vol 1953. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-9145-7_4
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DOI: https://doi.org/10.1007/978-1-4939-9145-7_4
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