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.
Used extensions & nodes
Created with KNIME Analytics Platform version 4.3.1
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