This workflow snippet demonstrates how to use a trained bioactivity model to predict the bioactivity of new molecules. The model was trained in the previous workflow snippet "Machine Learning Chemistry" (see https://kni.me/w/aJOlJNgWjHwAUnP5) and is read in using the Model Reader node. Similar to the previouse workflow snippet, the RDKit fingerprint is calculated for each molecule and the Random Forest Predictor applies the model on the new molecules. The results can be inspected in the "Visualise Prediction" component.
Used extensions & nodes
Created with KNIME Analytics Platform version 4.4.1
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