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Please clarify how you did the train test split – was it 80/20 per MOA? (which then works out to be ~78/22) What do you do with MOAs with few compounds? How do you handle compounds with multiple MOAs
Please plot a graph similar to the first one, reporting the "polypharmacology" i.e. number of MOAs per compound (X = number of MOAs of that a compound is annotated with; Y = number of compounds)
How do you assign a label? Presumably not a max because that would give you only one label.
MOA Multi-label Classification Predictions
@gway @shntnu
- Above figure interpretation
Overall Model Prediction results
- Model predictions with respect to MOA distribution among the 1,398 distinct compounds
Top predicted MOAs based on Precision-Recall AUC score
- Cell painting
- L1000
- Cell painting & L1000
30 different MOAs with higher ROC-AUC score in one profiling assay than in another one
- 76 MOAs have higher ROC AUC score in Cell painting than in L1000 and Integrated Cell painting & L1000 level 4 data
- 49 MOAs have higher ROC AUC score in Integrated Cell painting & L1000 than in L1000 and Cell painting level 4 data
- 53 MOA have higher ROC-AUC score in L1000 than in Cell painting and Integrated Cell painting & L1000 level 4 data
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