Investigate additional applications of explainable graph neural networks to other classes of bioentities other than just drugs and diseases (eg. phenotype prediction from groups of proteins, polypharmaceutical adverse events, etc.)
[ ] Come up more such example applications (other link predictions problems, node label prediction, etc.)
[ ] Find associated training data (this is the hard part)
Could possibly use predicates in KG2 (along with their antonyms) to generate TP/TN training data.
Investigate additional applications of explainable graph neural networks to other classes of bioentities other than just drugs and diseases (eg. phenotype prediction from groups of proteins, polypharmaceutical adverse events, etc.)
Could possibly use predicates in KG2 (along with their antonyms) to generate TP/TN training data.