DeepDDI

class DeepDDI(*, drug_channels, hidden_channels=2048, hidden_layers_num=9, out_channels=1)

Bases: chemicalx.models.base.Model

An implementation of the DeepDDI model from [ryu2018].

See also

This model was suggested in https://github.com/AstraZeneca/chemicalx/issues/2

ryu2018

Ryu, J. Y., et al. (2018). Deep learning improves prediction of drug–drug and drug–food interactions. Proceedings of the National Academy of Sciences, 115(18), E4304–E4311.

Methods Summary

forward(drug_features_left, drug_features_right)	Run a forward pass of the DeepDDI model.
unpack(batch)	Return the context features, left drug features and right drug features.

Methods Documentation

forward(drug_features_left, drug_features_right)

Run a forward pass of the DeepDDI model.

Parameters

• drug_features_left (FloatTensor) – A matrix of head drug features.

• drug_features_right (FloatTensor) – A matrix of tail drug features.

Return type

FloatTensor

Returns

A column vector of predicted interaction scores.

unpack(batch)

Return the context features, left drug features and right drug features.