This workflow demonstrates model building for a bioactivity data set with several machine learning methods and binary fingerprints of molecules.
The input data needs molecules in an SD file and a column containing the activity (the outcome that should be predicted). A fingerprint type can be chosen and set in the configuration. A report summarizing the input data and the modeling results can be downloaded after the workflow completion.
To use this workflow in KNIME, download it from the below URL and open it in KNIME:
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