AstraZeneca/chemicalx

Add the MatchMaker model

cthoyt opened this issue · 0 comments

Dear @andrejlamov,

  • Please read the paper first. It is here.
  • There is also code-release with the paper here.
  • After that read the contributing guidelines.
  • If there is an existing open-source version of the model please take a look.
  • ChemicalX is built on top of PyTorch 1.10. and torchdrug.
  • A similar model is DeepSynergy which usesFeedForward neural network to generate drug representations. Take a look at the layer definition here.
  • The library heavily builds on top on torchdrug and molecules in batches are PackedGraphs.
  • There is already a model class under ./chemicalx/models/
  • Context features, drug level features, and labels are all FloatTensors.
  • Look at the examples and tests under ./examples/ and ./tests/.
  • Add auxiliary layers as you see fit - please document these, add tests, and add these layers to the main readme.md if needed.
  • Add typing to the initialization and forward pass.
  • Non-data-dependent hyper-ammeters should have default values.
  • Please add tests under ./tests/ and make sure that your model/layer is tested with real data.
  • Write an example under ./examples/. What is the AUC on the test set? Is it reasonable?