Generate ChEMBL Predictions
Generate predictions with ONNX
This workfow uses a multitask neural network built using PyTorch and saved to the ONNX format to generate predictions.
The network generates predictions for bioactivity against 560 targets. The results are visually presented in a bisorted heatmap.
The workflow also looks up whatever information is available in ChEMBL itself about the activity of the prediction compounds on the 560 targets and presents that in a second interactive view.
NOTE that in order to use this workflow you also need the contents of the Data folder, which contains the saved network and information about the targets that are being predicted.
Nodes
- Column Filter9 ×
- Column Appender4 ×
- Column Resorter4 ×
- Column Rename3 ×
- Transpose3 ×
- Concatenate2 ×
- File Reader (Complex Format)2 ×
- GET Request2 ×
- JSON Path2 ×
- Joiner2 ×
- Reference Column Filter2 ×
- Reference Column Resorter2 ×
- Renderer to Image2 ×
- Row Filter2 ×
- Row Splitter2 ×
- Sorter2 ×
- Statistics2 ×
- String Manipulation2 ×
- Table View (JavaScript)2 ×
- Unpivoting2 ×
- Bubble Chart (Plotly)1 ×
- Column Rename (Regex)1 ×
- Expand Bit Vector1 ×
- Extract Column Header1 ×
- GroupBy1 ×
- Heatmap (JavaScript)1 ×
- Insert Column Header1 ×
- Missing Value Column Filter1 ×
- Python Script (legacy)1 ×
- RDKit Fingerprint1 ×
- RDKit To InChI1 ×
- TensorFlow Network Executor1 ×
- TensorFlow Network Reader1 ×
- Tile View (JavaScript)1 ×
Extensions
- FeatureKNIME Base nodes
- FeatureKNIME Deep Learning - TensorFlow Integration
- FeatureKNIME JavaScript Views
- FeatureKNIME JavaScript Views (Labs)
- FeatureKNIME Javasnippet
- Show all 11 modules