DeepSynergy

class DeepSynergy(*, context_channels, drug_channels, input_hidden_channels=32, middle_hidden_channels=32, final_hidden_channels=32, out_channels=1, dropout_rate=0.5)

Bases: chemicalx.models.base.Model

An implementation of the DeepSynergy model from [preuer2018].

See also

This model was suggested in https://github.com/AstraZeneca/chemicalx/issues/16

preuer2018

Preuer, K., et al. (2018). DeepSynergy: predicting anti-cancer drug synergy with Deep Learning. Bioinformatics, 34(9), 1538–1546.

Methods Summary

forward(context_features, …)	Run a forward pass of the DeepSynergy model.
unpack(batch)	Return the context features, left drug features, and right drug features.

Methods Documentation

forward(context_features, drug_features_left, drug_features_right)

Run a forward pass of the DeepSynergy model.

Parameters

• context_features (FloatTensor) – A matrix of biological context features.

• 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 synergy scores.

unpack(batch)

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